Lời dẫn

+ Bonjour à tous, Mesdames et messieurs,

et bienvenue à cet atelier important de réflexion et d’écriture du projet, sur la transition écologique dans les universités au Vietnam.

Je suis Phan Tú, venant de l’Université de Thuongmai. En effet, c’est un grand honneur pour notre Université d’organiser cet événement, aussi pour moi-même, d’y participer en tant que coordinateur.

Notre atelier d’aujourd’hui compte la participation de l’AUF – Agence Universitaire de la Francophonie, ainsi que des universités partenaires vietnamiennes, françaises et portugaises. Selon le plan d’actions, tout à l’heure, nous allons faire un tour de table pour la présentation des participants.

Maintenant, Mesdames et messieurs, permettez-moi de vous présenter Monsieur Nguyễn Hoàng – recteur de notre Université de Thuongmai, qui aura quelques mots pour officiellement débuter cet atelier. Je vous en prie, Monsieur !

+ Merci M. le recteur,

Nous avons écouté Monsieur le recteur de notre Université de Thuongmai. Il s’engage et dirigera directement la réalisation du futur projet souhaité au Vietnam, et particulièrement à notre Université. Maintenant, pour faire connaissance, nous allons procéder à un tour de table pour que chaque participant puisse se présenter lui-même à tout le monde.

Ici c’est le recteur de Notre Université de Thuongmai – M. Nguyễn Hoàng, que je vous l’ai présenté. Je suis Phan Tú, venant aussi de l’Université de Thuongmai, en tant que coordinateur de ce projet.

+ On va continuer avec Madame NGUYEN Thi Thuy Nga – responsable de projets chez AUF Asie-Pacifique, puis Monsieur Claude-Emmanuel LEROY– Secrétariat général de l’AUF, tous deux qui ont énormément contribué à ce projet.

Je vous en prie, d’abord Madame Nga !

+ Merci à tous, nous aurons l’occasion de faire plus connaissance pendant la pause et le déjeuner tout à l’heure.

Maintenant, j’invite Monsieur Claude-Emmanuel LEROY à faire le bilan du travail produit à ce jour, avant de discuter de la définition et de la structuration des actions à développer dans le projet.

+ Merci Claude,

je vous invite à discuter de la définition et de la structuration des actions à développer dans le projet, selon le formulaire de candidature produit à ce jour.

+ Maintenant, chaque université partenaire va présenter sa situation actuelle dans la perspective de transition écologique, par exemple sur ce qu’on est en train de faire, ce qu’on veut et va faire, quelle sont les difficultés rencontrées, etc….

Maintenant, chaque université partenaire va présenter sa situation actuelle dans la perspective de la transition écologique, par exemple ce qu’elle est en train de faire, ce qu’elle souhaite et va faire, les difficultés qu’elle a rencontrées, etc.

Après chaque présentation, je pense que tous les participants peuvent des questions s’il y en a, et nous pouvons immédiatement discuter de la situation actuelle de l’université concernée, bien sûr, si possible, en relation avec les contenus du formulaire de candidature du projet.

+ À la fin de ce matin, on a écouté la situation actuelle envers la transition écologique de la part de l’Université Thuongmai et ….

Pour cet après-midi, nous continuerons à écouter les autres partenaires. Je vous prie d’écouter l’université X

Plan d’actions

Atelier de réflexion et d’écriture du projet

 

Université Thuongmai (UTM)

salle de réunion, bâtiment F, 6ème étage – 79 rue Ho Tung Mau – Hanoi

 

 

Différents documents ont été produits depuis mars 2023 avec pour objectif de préparer les échanges, dans une approche participative et inclusive, au service d’une réflexion partagée nécessaire à la rédaction du formulaire Erasmus + RCES qui sera déposé le 16 février 2024.

 

Le dossier doit constituer une réponse aux priorités définies par le ministère de l’Éducation et de la Formation du Vietnam (MEF) dans la décision No.2718/QD-BGDDT le 21 septembre 2022. Il s’agit notamment de construire un modèle d’université écoresponsable avec une approche écologique.

 

En ce qui concerne le Programme Erasmus+ 2021-2027 de l’UE, il s’agit de mettre en place des partenariats (volet 2) pour la transformation dans l’enseignement supérieur dans le cadre de projets complexes et innovants de renforcement des capacités fondés sur un transfert d’expérience, de compétences et de bonnes pratiques, avec une série d’activités interconnectées qui visent à renforcer les capacités des établissements d‘enseignement supérieure et de recherche ciblés pour relever les défis du XXIe siècle, notamment le changement climatique et la gouvernance.

 

 

Lundi 2 octobre 2023

 

 

8h30 : Accueil des participants

9h00 : lancement des travaux

 

Mots de bienvenu de Monsieur Nguyen Hoang, recteur de l’UTM

 

9h15 : Début de travaux

 

Modérateurs : UTM et AUF

 

  • Tour de table pour une présentation des participant.es partenaires du projet.
  • Bilan du travail produit à ce jour en relation avec la partie B (description technique narrative) du formulaire de candidature.
  • Précisions à apporter en vue de finaliser la définition et la structuration des actions à développer dans le projet.

 

10h30 : Pause

10h45 : Suite des travaux

 

Modérateurs : UTM et AUF

 

  • Présentation par chaque partenaire des activités réalisées dans le cadre de leur plan stratégique de développement dans le domaine de la transition écologique.

 

Pour les partenaires vietnamiens ;

  • Université Thuongmai
  • Ecole supérieure de transport et de communication
  • Université Thu Dau Mot
  • Académie nationale d’aministration pubilque
  • Université Thang Long
  • Université vietnamo-coréenne de technologie d’information et de communication

 

Pour les partenaires européens :

  • Université de Rennes
  • Université Coimbra
  • CY Cergy Paris université
  • Université Bordeaux Montaigne

 

12h30 : Pause déjeunée – Déjeuner offer par l’UTM

14h30 : Reprise des travaux

 

Modérateurs : UTM et AUF

 

Pour rappel, le projet (PROVIDENTIEL) vise un accompagnement des établissements d’enseignement supérieur vietnamiens dans la définition et la mise en œuvre d’un système de management environnemental (gouvernance universitaire rénovée) destiné à améliorer la performance environnementale (transition écologique) des activités qu’ils développement (formation, recherche, partenariats, etc.), et ceci en tenant compte des spécificités de leur écosystème (développement inclusif et soutenable).

 

À ce stade de la définition du projet, et dans le prolongement des réflexions de la matinée, il s’agit d’identifier :

 

  • Les aspects de la gouvernance universitaires, à identifier pour chaque phase (Planifier-Déployer-Contrôler-Améliorer – PDCA) du projet, qui nécessitent un renforcement des capacités fondés sur un transfert d’expérience, de compétences et de bonnes pratiques au service d’un système de management environnemental à contextualiser ;
  • Les domaines de l’EES (recherche, formation, ressources humaines, infrastructures, finances, communication, système d’information, services à la communauté, partenariat, etc.) sur lesquels va porter en priorité le système de management environnemental;
  • Les composantes de la transition écologique (consommation et achats responsables, gestion des déchets, optimisation de la consommation d’eau et d’énergie, etc.) sur lesquels va porter en priorité le système de management environnemental.

 

15h45 : Pause

16h00 : Suite des travaux

 

Modérateurs : UTM et AUF

 

  • Poursuite et finalisation des échanges par l’identification des activités jugées prioritaires à intégrer dans le projet.

 

17h30 : Fin des travaux de la journée

 

 

 

Mardi 3 octobre 2023

 

 

Dans la continuité de travail produit la veille, il s’agit de mettre en place des échanges, dans une approche participative et inclusive, au service de la définition de certains lots d’activités :

 

  • WP2 : de l’analyse des spécificités de l’EES et de son écosystème à la définition du plan stratégique de développement en matière de performance environnementale.
  • WP3 : de la définition du plan stratégique de développement en matière de performance environnementale à la mise en place d’actions opérationnelles.
  • WP4 : de l’évaluation des résultats des plans d’action opérationnels à l’identification des dysfonctionnements, puis de l’identification des dysfonctionnements à la mise en œuvre de mesures correctrices

 

Pour rappel, l’approche Planifier-Déployer-Contrôler-Améliorer (PDCA) sert de guide à la définition et la mise en œuvre d’un système de management environnemental qui tient compte des spécificités de chaque EES, et donc des activités qu’il développe en relation avec son écosystème.

 

Autre élément clé pour garantir la cohérence du projet, la méthodologie du projet s’appuie sur un séquençage de chaque phase :

 

·         Séquence 1 : échanges dans une logique inclusive de co-construction de la méthode et des outils ;

·         Séquence 2 : mise en œuvre et d’accompagnement au changement (offre de formation) ;

·         Séquence 3 : bilan des résultats obtenus comprenant une auto-évaluation par les responsables du lot suivie d’un audit par le Comité d’audit interne (AI) ;

·         Séquence 4 : Phase de clôture et de lancement du lot suivant.

 

Le séquençage est le résultat d’une planification établie sur la base d’une liste des principales activités, regroupées en lots d’activités (WP), au service des résultats attendus et mesurables. Ce séquençage permet l’identification des temps d’échanges et de partage d’expériences entre EES, des temps de formations nécessaires à l’appropriation, des temps de synchronisation entre les équipes mobilisées pour telles ou telles activités et les séquences de validation permettant de lancer une nouvelle activité.

 

Au-delà de la définition d’un chronogramme d’activités, le séquençage de chaque phase du projet permet enfin de dresser un inventaire des ressources (humaines, matérielles, etc.) à mobiliser pour chaque activité, y compris l’expertise à mobiliser, et donc de tenir compte de la charge de travail de chacune des parties prenantes. Ce qui valorise l’implication et la responsabilité de tous les EES partenaires et des parties prenantes dès l’élaboration du projet et jusqu’à son évaluation.

 

 

A noter que le WP5 vise un renforcement des compétences des personnels au sein des EES partenaires et un accompmagnement à la conduite au changement. La sensibilisations et l’offre de formation sont mise en œuvre par les responsables des WP2, 3 et 4 dans le cadre d’un accompagnement (séquence 2 de chaque lot) dans la mise en place efficace et effective des activités du projet.

 

9h00 : Début de travaux

 

Modérateurs : Université de Rennes et Ecole supérieure de transport et de communication

 

Phase de planification (A) – WP2 : de l’analyse de l’écosystème à la définition du plan stratégique de développement en matière de performance environnementale

 

Cette phase doit notamment permettre à chaque EES de réunir les conditions institutionnelles préalables à la définition et la mise en place d’un système de management environnemental en relation avec les objectifs qu’il s’est fixés en matière de performance environnementale. Cette phase tient également compte des spécificités (contextes interne et externe, degré d’autonomie) de chaque EES et des attentes des parties prenantes de son écosystème.

 

12h30 : Pause déjeunée à l’université

14h30 : Reprise des travaux

 

Modérateurs : Université de Rennes et Ecole supérieure de transport et de communication

 

Suite des travaux sur la phase de planification

15h45 : Pause

16h00 : Suite des travaux

 

Modérateurs : Université de Rennes et Ecole supérieure de transport et de communication

 

Fin des travaux sur la phase de planification

 

17h30 : Fin des travaux de la journée

 

 

Mercredi 4 octobre 2023

 

La matinée est consacrée à la visite de deux universités hanoïennes partenaires du projet avec pour objectifs de  pousuivre les échanges inititiés lors du lancement des enquêtes (mai – juillet 2023) et de l’analyse des résultats.

 

9h-10h

Académie nationale d’administration publique

Adresse : 77, Nguyễn Chí Thanh, Láng Thượng, Đống Đa, Hà Nội

Accueil des participants par Monsieur XXXXX, vice-Recteur

Contact : Madame Tran Thi Lan Anh – directrice adjointe de la coopération internationale

 

10h30-11h30

Ecole supérieure de transport et de communication

Adresse : Lang Thuong, Cau Giay – Hanoi

Accueil des participants par Monsieur Le Hoai Duc, vice-Recteur

Contact : Monsieur Duong Huu Tuyen – directeur adjoint de l’accréditation et de l’assurance qualité

 

12h30 : Pause déjeunée à l’UTM

14h30 : Reprise des travaux

 

Modérateurs : CY Cergy Paris Université et l’Université vietnamo-coréenne de technologie d’information et de communication

Phase de déploiement (B)  –  WP3 : de la définition du plan stratégique de développement en matière de performance environnementale à la mise en place d’actions opérationnelles

Il s’agit pour chaque EES de mettre en œuvre les moyens de maîtrise identifiés en vue d’atteindre ses objectifs environnementaux, tels que définis ou à redéfinir dans leurs plans stratégiques de développement en matière de performance environnementale, et de réaliser les actions à développer. Les moyens de maîtrise peuvent inclure des moyens techniques et des procédures, et peuvent être mis en œuvre suivant une hiérarchie chronologique, de manière séparée ou combinée.

Dans toutes les hypothèses, il s’agit de définir séquensage du lot d’activités qui doit assurer le passage de de la définition du plan stratégique de développement en matière de performance environnementale à la mise en place d’actions opérationnelles,

 

Pour rappel, la méthodologie du projet s’appuie sur un séquençage de chaque phase :

 

·         Séquence 1 : échanges dans une logique inclusive de co-construction de la méthode et des outils ;

·         Séquence 2 : mise en œuvre et d’accompagnement au changement (offre de formation) ;

·         Séquence 3 : bilan des résultats obtenus comprenant une auto-évaluation par les responsables du lot suivie d’un audit par le Comité d’audit interne (AI) ;

·         Séquence 4 : Phase de clôture et de lancement du lot suivant.

 

Le séquençage est le résultat d’une planification établie sur la base d’une liste des principales activités, regroupées en lots d’activités (WP), au service des résultats attendus et mesurables. Ce séquençage permet l’identification des temps d’échanges et de partage d’expériences entre EES, des temps de formations nécessaires à l’appropriation, des temps de synchronisation entre les équipes mobilisées pour telles ou telles activités et les séquences de validation permettant de lancer une nouvelle activité.

 

Au-delà de la définition d’un chronogramme d’activités, le séquençage de chaque phase du projet permet également de dresser un inventaire des ressources (humaines, matérielles, etc.) à mobiliser pour chaque activité, y compris l’expertise à mobiliser, et donc de tenir compte de la charge de travail de chacune des parties prenantes. Ce qui valorise l’implication et la responsabilité de tous les EES partenaires et des parties prenantes dès l’élaboration du projet et jusqu’à son évaluation.

 

 

15h45 : Pause

16h00 : Suite des travaux

 

Modérateurs : CY Cergy Paris Université et l’Université vietnamo-coréenne de technologie d’information et de communication

Suite des travaux sur la phase de déploiement

15h45 : Pause

16h00 : Suite des travaux

 

Modérateurs : CY Cergy Paris Université et l’Université vietnamo-coréenne de technologie d’information et de communication

Fin des travaux sur la phase de déploiement

17h30 : Fin des travaux de la journée

 

 

Jeudi 5 octobre 2023

9h00 : Début de travaux

Modérateurs : Université Coimbra et Académie nationale d’administration publique

Phase de contrôle et d’amélioration de la performance environnementale (C) – WP4 : de l’évaluation des résultats des plans d’actions opérationnels à l’identification des dysfonctionnements au service de la définition et la mise en œuvre de mesures correctrices

En complément de l’analyse des risques décrit lors de la phase précédente, une phase de contrôle est mise en place : il s’agit de mettre en œuvre un dispositif d’identification des sources potentielles de dysfonctionnement ou de blocage pour permettre la définition de mesures correctives à prendre dans le cadre d’une amélioration continue de la performance environnementale des EES.

Il s’agit surtout de rendre compte aux groupes cibles des activités développées par chaque EES pour la définition et la mise en œuvre du système de management environnemental ; ce qui suppose de mesurer l’atteinte des résultats attendus, et donc de recueillir, traiter et restituer les informations et indicateurs pertinents. Les données quantitatives et qualitatives recueillies constituent la base du rapport de restitution.

Au-delà de l’amélioration continue du système de management environnemental et de la cohérence des moyens de maîtrise mobilisés, il s’agit surtout, d’une part, de prendre les décisions nécessaires relatives aux éventuels changements à apporter au système de management environnemental (y compris les ressources) et, d’autre part, d’identifier les actions à mener lorsque les objectifs n’ont pas été atteints. Dans un cas comme dans l’autre, les décisions sont à prendre dans une approche participative.

Pour rappel, la méthodologie du projet s’appuie sur un séquençage de chaque phase :

 

·         Séquence 1 : échanges dans une logique inclusive de co-construction de la méthode et des outils ;

·         Séquence 2 : mise en œuvre et d’accompagnement au changement (offre de formation) ;

·         Séquence 3 : bilan des résultats obtenus comprenant une auto-évaluation par les responsables du lot suivie d’un audit par le Comité d’audit interne (AI) ;

·         Séquence 4 : Phase de clôture et de lancement du lot suivant.

 

Le séquençage est le résultat d’une planification établie sur la base d’une liste des principales activités, regroupées en lots d’activités (WP), au service des résultats attendus et mesurables. Ce séquençage permet l’identification des temps d’échanges et de partage d’expériences entre EES, des temps de formations nécessaires à l’appropriation, des temps de synchronisation entre les équipes mobilisées pour telles ou telles activités et les séquences de validation permettant de lancer une nouvelle activité.

 

Au-delà de la définition d’un chronogramme d’activités, le séquençage de chaque phase du projet permet également de dresser un inventaire des ressources (humaines, matérielles, etc.) à mobiliser pour chaque activité, y compris l’expertise à mobiliser, et donc de tenir compte de la charge de travail de chacune des parties prenantes. Ce qui valorise l’implication et la responsabilité de tous les EES partenaires et des parties prenantes dès l’élaboration du projet et jusqu’à son évaluation.

 

 

12h : Pause déjeunée à l’UTM

14h30 : Reprise des travaux

15h45 : Pause

16h00 : Suite des travaux

 

WP5 : Renforcement des compétences des personnels au sein des EES partenaires et conduite au changement

Responsable : Sensibilisations et offres de formation dispensées par des responsables des WP2, 3 et 4 dans le cadre d’un accompagnement dans la mise en place efficace et effective des activités du projet (séquence 2 de chaque lot).

 

17h30 : Fin des travaux de la journée

 

 

Vendredi 6 octobre 2023

 

Dans la continuité de travail produit la veille, il s’agit de mettre en place des échanges, dans une approche participative et inclusive, au service de la rédaction du formulaire.

 

9h00 : Début de travaux

 

Modérateurs : Université Bordeaux Montaigne

WP7 : Diffusion et exploitations des résultats (diffusion du guide d’accompagnement)

Responsable : Université Bordeaux Montaigne

Soutien : AUF

 

10h30 : Pause

10h45 : Suite des travaux

 

  • Événements, réunions et mobilité
  • Calendrier (projets de plus de 2 ans)

 

12h30 : Pause déjeunée à l’université

14h30 : Reprise des travaux

 

Modérateurs : UTM et AUF

  • Présentation du calendrier lié au dépôt du dossier.
  • Rédaction + correction du formulaire : qui produit quoi et quand ?

 

15h45 : Pause

16h00 : Suite des travaux

 

17h30 : Fin des travaux de la journée

 

Learn Programming Languages (JavaScript, Python, Java, PHP, C, C#, C++, HTML, CSS)

There’s no question that software programming is a hot career right now. The U.S. Bureau of Labor Statistics projects 21 percent growth for programming jobs from 2018 to 2028, which is more than four times the average for all occupations. What’s more, the median annual pay for a software programmer is about $106,000, which nearly three times the median pay for all U.S. workers.

Not all programming jobs are the same, however. Different roles, companies, and types of software require knowing and understanding different programming languages—and it’s often beneficial to know multiple languages. Trying to break into the field of software programming can be a daunting experience, especially for professionals with no prior programming experience.

Whether you’re new to programming or looking to brush up on your skills, it helps to know which languages are in high demand. Here are 10 of the most popular programming languages of 2020 based on the number of job postings listed on job search site Indeed, the average annual salary for those jobs, and factors such as ease of use and potential for growth.

Top 10 Most Popular Programming Languages

1. Python

Top 10 Popular Programming Languages Chart

Number of jobs: 19,000

Average annual salary: $120,000

Benefits: Python is widely regarded as a programming language that’s easy to learn, due to its simple syntax, a large library of standards and toolkits, and integration with other popular programming languages such as C and C++. In fact, it’s the first language that students learn in the Align program, Gorton says. “You can cover a lot of computer science concepts quickly, and it’s relatively easy to build on.” It is a popular programming language, especially among startups, and therefore Python skills are in high demand.

Drawbacks: Python is not suitable for mobile application development.

Common uses: Python is used in a wide variety of applications, including artificial intelligence, financial services, and data science. Social media sites such as Instagram and Pinterest are also built on Python.

2. JavaScript

Number of jobs: 24,000

Average annual salary: $118,000

Benefits: JavaScript is the most popular programming language for building interactive websites; “virtually everyone is using it,” Gorton says. When combined with Node.js, programmers can use JavaScript to produce web content on the server before a page is sent to the browser, which can be used to build games and communication applications that run directly in the browser. A wide variety of add-ons extend the functionality of JavaScript as well.

Drawbacks: Internet browsers can disable JavaScript code from running, as JavaScript is used to code pop-up ads that in some cases can contain malicious content.

Common uses: JavaScript is used extensively in website and mobile application development. Node.js allows for the development of browser-based applications, which do not require users to download an application.

3. Java

Number of jobs29,000

Average annual salary: $104,000

Benefits: Java is the programming language most commonly associated with the development of client-server applications, which are used by large businesses around the world. Java is designed to be a loosely coupled programming language, meaning that an application written in Java can run on any platform that supports Java. As a result, Java is described as the “write once, run anywhere” programming language.

Drawbacks: Java is not ideal for applications that run on the cloud, as opposed to the server (which is common for business applications). In addition, the software company Oracle, which owns Java, charges a licensing fee to use the Java Development Kit.

Common uses: Along with business applications, Java is used extensively in the Android mobile operating system.

4. C#

Number of jobs: 18,000

Average annual salary: $97,000

Benefits: Microsoft developed C# as a faster and more secure variant of C. It is fully integrated with Microsoft’s .NET software framework, which supports the development of applications for Windows, browser plug-ins, and mobile devices. C# offers shared codebases, a large code library, and a variety of data types.

Drawbacks: C# can have a steep learning curve, especially for resolving errors. It is less flexible than languages such as C++.

Common uses: C# is the go-to language for Microsoft ad Windows application development. It can also be used for mobile devices and video game consoles using an extension of the .NET Framework called Mono.

5. C

Number of jobs: 8,000

Average annual salary: $97,000

Benefits: Along with Python and Java, C forms a “good foundation” for learning how to program, Gorton says. As one of the first programming languages ever developed, C has served as the foundation for writing more modern languages such as Python, Ruby, and PHP. It is also an easy language to debug, test, and maintain.

Drawbacks: Since it’s an older programming language, C is not suitable for more modern use cases such as websites or mobile applications. C also has a complex syntax as compared to more modern languages.

Common uses: Because it can run on any type of device, C is often used to program hardware, such as embedded devices in automobiles and medical devices used in healthcare.

6. C++

Number of jobs: 9,000

Average annual salary: $97,000

Benefits: C++ is an extension of C that works well for programming the systems that run applications, as opposed to the applications themselves. C++ also works well for multi-device and multi-platform systems. Over time, programmers have written a large set of libraries and compilers for C++. Being able to use these utilities effectively is just as important to understanding a programming language as writing code, Gorton says.

Drawbacks: Like C, C++ has complex syntax and an abundance of features that can make it complicated for new programmers. C++ also does not support run-time checking, which is a method of detecting errors or defects while software is running.

Common uses: C++ has many uses and is the language behind everything from computer games to mathematical simulations.

7. Go

Number of jobs1,700

Average annual salary: $93,000

Benefits: Also referred to as Golang, Go was developed by Google to be an efficient, readable, and secure language for system-level programming. It works well for distributed systems, in which systems are located on different networks and need to communicate by sending messages to each other. While it is a relatively new language, Go has a large standards library and extensive documentation.

Drawbacks: Go has not gained widespread use outside of Silicon Valley. Go does not include a library for graphical user interfaces, which are the most common ways that end-users interact with any device that has a screen.

Common uses: Go is used primarily for applications that need to process a lot of data. In addition to Google, companies using Go for certain applications include Netflix, Twitch, and Uber.

8. R

Number of jobs: 1,500

Average annual salary: $93,000

Benefits: R is heavily used in statistical analytics and machine learning applications. The language is extensible and runs on many operating systems. Many large companies have adopted R in order to analyze their massive data sets, so programmers who know R are in great demand.

Drawbacks: R does not have the strict programming guidelines of older and more established languages.

Common uses: R is primarily used in statistical software products.

9. Swift

Number of jobs1,800

Average annual salary: $93,000

Benefits: Swift is Apple’s language for developing applications for Mac computers and Apple’s mobile devices, including the iPhone, iPad, and Apple Watch. Like many modern programming languages, Swift has a highly readable syntax, runs code quickly, and can be used for both client-side and server-side development.

Drawbacks: Swift can only be used on newer versions of iOS 7 and will not work with older applications. As a newer programming language, the code can be unstable at times, and there are fewer third-party resources available to programmers.

Common uses: Swift is used for iOS and macOS applications.

10. PHP

Number of jobs7,000

Average annual salary$81,000

Benefits: PHP is widely used for server-side web development, when a website frequently requests information from a server. As an older language, PHP benefits from a large ecosystem of users who have produced frameworks, libraries, and automation tools to make the programming language easier to use. PHP code is also easy to debug.

Drawbacks: As Python and JavaScript have gained popularity, PHP’s popularity has dropped. PHP is also known for its security vulnerabilities. According to Indeed, most PHP programmers take short-term roles that last less than one year.

Common uses: PHP is the code running content-oriented websites such as Facebook, WordPress, and Wikipedia.

7 Other Programming Languages to Consider

The following programming languages aren’t quite as popular as the 10 listed above, but they are also worth considering if you’re looking to expand your programming options.

  • Dart is optimal for programming applications that need to run on multiple platforms, such as Windows and iOS.
  • Kotlin is used to develop applications for the Android OS.
  • MATLAB is a proprietary language developed by MathWorks and used for scientific research and numerical computing.
  • Perl got its start for programming text, which makes it easy to learn and popular for developing a proof of concept.
  • Ruby is losing traction as compared to other languages, but the Ruby on Rails framework was influential to other, later Web application frameworks for Python, PHP, and JavaScript.
  • Rust emphasizes high performance and security and is useful for applications where many things are happening concurrently.
  • Scala, named as a play on scalable language, is compatible with Java and is useful for cloud-based applications.

Which Programming Language Should You Learn?

Some programmers are able to build a career out of being an expert in one language, but many programmers learn new languages frequently, Gorton says. It’s not uncommon for a professional programmer to be fluent in three or four different languages, he adds.

The type of software you want to develop is one consideration for which programming languages to learn. While there are no concrete rules for what language is used to write what software, a few trends offer some guidance:

  • Web-based startups are more likely to be programming in Python and JavaScript.
  • Larger companies tend to develop their internal software applications using C# or Java and their Web applications using PHP.
  • Programs for data analytics typically use the R and MATLAB programming languages.
  • Embedded devices, such as those in the automotive and healthcare industries, run software written in C, C++, or Rust.
  • Applications that run on the cloud are increasingly written in Go or Scala.
  • Mobile applications are increasingly written in Swift or Kotlin.

Source: Brian Eastwood

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Create your professional WordPress website without code

A WordPress website is any website that uses WordPress as its content management system (CMS). WordPress powers both the backend of the website (the interface where a user logs in to make changes or add new content) and the frontend (the visible part of the website that your visitors see on the web).

Here are just a few examples of the types of websites you can build with WordPress:

  • Blog – A blog is a special type of website devoted to sharing thoughts, photos, reviews, tutorials, recipes and so much more. Blogs usually display the most recently-published content first.
  • E-commerce website – An e-commerce website allows you to sell goods or services online and collect payment via an online payment system. You can download and install a WordPress e-commerce plugin to extend the default functionality of WordPress so you can have an online store on your website.
  • Business website – Many businesses will benefit from having an online presence in the form of their own website. If your business needs a website for customers to learn about your company and what you have to offer, WordPress is an excellent option. Customers can contact you, ask for a quote, schedule an appointment and much more.
  • Membership website – A membership website allows you to put content behind a paywall or an account login. To access pages or posts, users must login or pay for the content. WordPress can also handle membership websites with additional plugins.
  • Portfolio website – Show off your artwork, design skills and more with a portfolio website built on WordPress.
  • Forum website – A forum website can be a helpful place for users to ask questions or share advice. Believe it or not, many forum websites run on WordPress.
  • Event website – Hosting an event? WordPress makes it easy for you to share your event details and sell tickets.
  • E-learning website – Students can take online courses, track their progress, download resources and much more from an e-learning website.
  • Wedding website – Share the details of your big day with a wedding website built on WordPress. With an array of WordPress wedding themes, you can get a website up quickly and easily.

The possibilities are endless when it comes to customizing a WordPress web. WordPress themes and plugins can add new design options and added functionality. Check out WordPress.org for free themes and plugins.

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Great Thinkers and their Big Ideas

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 0-9 & other

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A

Abba Lerner

Adam Smith

Albert Camus

Albert Einstein

Albert Hirschman

Alexius von Meinong

Alfred Jules Ayer

Alfred Marshall

Alfred North Whitehead

Alvin Hansen

Andre Gunder Frank

Antisthenes

Antoine Augustin Cournot

Antoine-Laurent Lavoisier

Antonio Gramsci

Archimedes

Aristotle

Arnold Geulincx

Arnold Toynbee

Arthur Cecil Pigou

Arthur Laffer

Arthur Okun

Arthur Schopenhauer

Auguste Comte

Ayn Rand

B

Baruch Spinoza

Benedetto Croce

Benito Mussolini

Bertil Ohlin

Bertrand Russell

Blaise Pascal

Boethius

C

Carl Friedrich Gauss

Carl Gustav Hempel

Carl Gustav Jung

Charles Bonnet

Charles Darwin

Charles Sanders Peirce

Charles Tiebout

Charles-Louis de Secondat Montesquieu

Che Guevara

Cicero

Comte de Buffon

Confucius

D

Daniel Bernoulli

Dante Alighieri

David Easton

David Hartley

David Hume

David Ricardo

Democritus

Desiderius Erasmus

Dimitri Ivanovich Mendeleev

Diogenes of Sinope

Donald Davidson

E

Edmund Burke

Edmund Husserl

Eduard Bernstein

Edward Chamberlin

Edward Sapir

Eli Heckscher

Emile Durkheim

Emile Durkheim

Empedocles

Epictetus

Epicurus of Samos

Erich Fromm

Erik Lindahl (1891-1960)

Ernst Engel (1821-1896)

Ernst Mach

Erving Goffman

Erwin Schrodinger

Euclid

Eugen Slutsky

Evsey Domar

F

Francis Bacon

Francis Edgeworth

Francis Galton

Francis Herbert Bradley

Francois Modigliani

Francois Perroux

Francois Quesnay

Frank Ramsey

Franz Brentano

Friedrich Engels

Friedrich Hayek

Friedrich Hegel

Friedrich Nietzsche

Friedrich Schleiermacher

G

Gabriel Marcel

Galileo Galilei

Gary Becker

George Arthur Akerlof

George Berkeley

George Douglas Howard Cole

George Edward Moore

George Fox

George Henry Lewes

George Herbert Mead

George Santayana

Georges Sorel

Gerard Debreu

Giambattista Vico

Gilbert Ryle

Gottfried Wilhelm Leibniz

Gottlob Frege

Gregor Johann Mendel

Gustav Cassel

H

Hans Singer

Hans-Georg Gadamer

Harold Hotelling

Henri Bergson

Henri Lefebvre

Henry David Thoreau

Henry More

Heraclitus of Ephesus

Herbert Simon

Herbert Spencer

Hilaire Belloc

Hilary Putnam

Hippocrates

Hollis Chenery

Hugo Grotius

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I

Immanuel Kant

Immanuel Wallerstein

Irving Fisher

Isaac Newton

Isaiah Berlin (1909-1997)

J

Jacob Viner

Jakob Bernoulli

James Buchanan

James Burnham

James Clerk Maxwell

James Tobin

Jean-Baptiste Say

Jean-Jacques Rousseau

Jean-Paul Sartre

Jeremy Bentham

Joan Robinson

Johann von Thunen

Johannes Kepler

John Bates Clark

John Calvin

John Dewey

John Henry Newman

John Hicks

John Langshaw Austin

John Locke

John Maurice Clark

John Maynard Keynes

John Muth

John Rawls

John Stuart Mill

John von Neumann

John W Burton

Jonathan Edwards

Jose Ortega Y Gasset

Joseph Bertrand

Joseph Schumpeter

Joseph Stalin

Jules Dupuit

Jules Henri Poincare

Jurgen Habermas

Jurgen Habermas

K

Karl Jaspers

Karl Marx

Karl Popper

Karl Rahner

Kenneth Arrow

Knut Wicksell

L

Leon Trotsky

Leon Walras

Leonhard Euler

Leucippus

Louis Bachelier

Louis-Auguste Blanqui

Lucretius

Ludwig von Mises

Ludwig Wittgenstein

Luitzen Egbertus Jan Brouwer

M

Mancur Olson

Mao Zedong

Marcus Aurelius

Marie Antoine Condorcet

Martin Buber

Martin Heidegger

Martin Luther

Mary Wollstonecraft

Maurice Allais

Max Planck

Max Weber

Meister Eckhart

Melissus of Samos

Michael Bakunin

Michael Dummett

Michal Kalecki

Michel de Montaigne

Miguel de Unamuno Y Jugo

Milton Friedman

Moritz Schlick

Mortimer Adler

Moses Maimonides

Nassau William

N

Nelson Goodman

Niccolo Machiavelli

Nicholas Copernicus

Nicholas Kaldor

Nicolas Malebranche

Nicos Poulantzas

Niels Bohr

Norbert Elias

O

Origen

P

Parmenides of Elea

Paul Baran

Paul Tillich

Paulo Freire

Peter Abelard

Peter Frederick Strawson

Philip Wicksteed

Piero Sraffa

Pierre Bayle

Pierre Bourdieu

Pierre Gassendi

Pierre Teilhard de Chardin

Pierre-Joseph Proudhon

Pierre-Maurice Duhem

Plato

Plotinus

Prince Peter Kropotkin

Protagoras

Ptolemy

Pythagoras of Samos

Ralph Barton Perry

Q

R

Ralph Cudworth

Ralph Waldo Emerson

Raul Prebisch

Reinhold Niebuhr

Rene Descartes

Richard Avenarius

Richard Kahn

Richard von Mises

Robert Barro

Robert Dahl

Robert Giffen

Robert Lucas

Robert Michels

Robert Mundell

Robert Solow

Robert Torrens

Robin George Collingwood

Rodney Barker

Ronald Coase

Ronald Reagan

Roy Harrod

Roy Wood Sellars

Rudolf Carnap

Rudolf Steiner

Rudolph Hermann Lotze

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S

Saint Anselm of Canterbury

Saint Augustine

Saint Bernard of Clairvaux

Saint Bonaventure

Saint John of the Cross

Saint Teresa of Avila

Saul Kripke

Sextus Empiricus

Sigmund Freud

Simone de Beauvoir

Simone Weil

Socrates

Soren Aabye Kierkegaard

O

Origen

P

Parmenides of Elea

Paul Baran

Paul Tillich

Paulo Freire

Peter Abelard

Peter Frederick Strawson

Philip Wicksteed

Piero Sraffa

Pierre Bayle

Pierre Bourdieu

Pierre Gassendi

Pierre Teilhard de Chardin

Pierre-Joseph Proudhon

Pierre-Maurice Duhem

Plato

Plotinus

Prince Peter Kropotkin

Protagoras

Ptolemy

Pythagoras of Samos

Ralph Barton Perry

Q

R

Ralph Cudworth

Ralph Waldo Emerson

Raul Prebisch

Reinhold Niebuhr

Rene Descartes

Richard Avenarius

Richard Kahn

Richard von Mises

Robert Barro

Robert Dahl

Robert Giffen

Robert Lucas

Robert Michels

Robert Mundell

Robert Solow

Robert Torrens

Robin George Collingwood

Rodney Barker

Ronald Coase

Ronald Reagan

Roy Harrod

Roy Wood Sellars

Rudolf Carnap

Rudolf Steiner

Rudolph Hermann Lotze

S

Saint Anselm of Canterbury

Saint Augustine

Saint Bernard of Clairvaux

Saint Bonaventure

Saint John of the Cross

Saint Teresa of Avila

Saul Kripke

Sextus Empiricus

Sigmund Freud

Simone de Beauvoir

Simone Weil

Socrates

Soren Aabye Kierkegaard

T

Talcott Parsons

Thomas Aquinas

Thomas De Quincey

Thomas Henry Huxley

Thomas Hobbes

Thomas Jefferson

Thomas Malthus

Thomas More

Thomas Paine

Thomas Reid

Thomas Samuel Kuhn

Thorstein Veblen

U

V

Vilfredo Pareto

Vladimir Ilyich Lenin

Voltaire

W

W.E.B. DuBois

Walter Heller

Wassily Leontief

Werner Heisenberg

Wilhelm Dilthey

Willard Van Orman Quine

William Baumol

William Blake

William Godwin

William James

William of Ockham

William Petty

X

Y

Z

Zeno of Citium

Zeno of Elea

0-9 & other

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Nature and scope of science

What is science?

Science (from the Latin word scientia, meaning “knowledge”)[1] is a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe.[2][3][4]

The earliest roots of science can be traced to Ancient Egypt and Mesopotamia in around 3500 to 3000 BCE.[5][6] Their contributions to mathematics, astronomy, and medicine entered and shaped Greek natural philosophy of classical antiquity, whereby formal attempts were made to provide explanations of events in the physical world based on natural causes.[5][6] After the fall of the Western Roman Empire, knowledge of Greek conceptions of the world deteriorated in Western Europe during the early centuries (400 to 1000 CE) of the Middle Ages[7] but was preserved in the Muslim world during the Islamic Golden Age.[8] The recovery and assimilation of Greek works and Islamic inquiries into Western Europe from the 10th to 13th century revived “natural philosophy”,[7][9] which was later transformed by the Scientific Revolution that began in the 16th century[10] as new ideas and discoveries departed from previous Greek conceptions and traditions.[11][12][13][14] The scientific method soon played a greater role in knowledge creation and it was not until the 19th century that many of the institutional and professional features of science began to take shape;[15][16][17] along with the changing of “natural philosophy” to “natural science.”[18]

Modern science is typically divided into three major branches that consist of the natural sciences (e.g., biology, chemistry, and physics), which study nature in the broadest sense; the social sciences (e.g., economics, psychology, and sociology), which study individuals and societies; and the formal sciences (e.g., logic, mathematics, and theoretical computer science), which study abstract concepts. There is disagreement,[19][20] however, on whether the formal sciences actually constitute a science as they do not rely on empirical evidence.[21] Disciplines that use existing scientific knowledge for practical purposes, such as engineering and medicine, are described as applied sciences.[22][23][24][25]

Science is based on research, which is commonly conducted in academic and research institutions as well as in government agencies and companies. The practical impact of scientific research has led to the emergence of science policies that seek to influence the scientific enterprise by prioritizing the development of commercial products, armaments, health care, and environmental protection.

Branches of science

Modern science is commonly divided into three major branches that consist of the natural sciences, social sciences, and formal sciences. Each of these branches comprise various specialized yet overlapping scientific disciplines that often possess their own nomenclature and expertise.[90] Both natural and social sciences are empirical sciences[91] as their knowledge is based on empirical observations and is capable of being tested for its validity by other researchers working under the same conditions.[92]

There are also closely related disciplines that use science, such as engineering and medicine, which are sometimes described as applied sciences. The relationships between the branches of science are summarized by the following table.

Science
Formal science Empirical sciences
Natural science Social science
Foundation Logic; Mathematics; Statistics Physics; Chemistry; Biology;
Earth science; Space science
Economics; Political science;
Sociology; Psychology
Application Computer science Engineering; Agricultural science;
Medicine; Dentistry; Pharmacy
Business administration;
Jurisprudence; Pedagogy

Natural science

The scale of the Universe mapped to branches of science and showing how one system is built atop the next through the hierarchy of the sciences.

Natural science is concerned with the description, prediction, and understanding of natural phenomena based on empirical evidence from observation and experimentation. It can be divided into two main branches: life science (or biological science) and physical science. Physical science is subdivided into branches, including physics, chemistry, astronomy and earth science. These two branches may be further divided into more specialized disciplines. Modern natural science is the successor to the natural philosophy that began in Ancient Greece. Galileo, Descartes, Bacon, and Newton debated the benefits of using approaches which were more mathematical and more experimental in a methodical way. Still, philosophical perspectives, conjectures, and presuppositions, often overlooked, remain necessary in natural science.[93] Systematic data collection, including discovery science, succeeded natural history, which emerged in the 16th century by describing and classifying plants, animals, minerals, and so on.[94] Today, “natural history” suggests observational descriptions aimed at popular audiences.[95]

Social science

Social science is concerned with society and the relationships among individuals within a society. It has many branches that include, but are not limited to, anthropology, archaeology, communication studies, economics, history, human geography, jurisprudence, linguistics, political science, psychology, public health, and sociology. Social scientists may adopt various philosophical theories to study individuals and society. For example, positivist social scientists use methods resembling those of the natural sciences as tools for understanding society, and so define science in its stricter modern sense. Interpretivist social scientists, by contrast, may use social critique or symbolic interpretation rather than constructing empirically falsifiable theories, and thus treat science in its broader sense. In modern academic practice, researchers are often eclectic, using multiple methodologies (for instance, by combining both quantitative and qualitative research). The term “social research” has also acquired a degree of autonomy as practitioners from various disciplines share in its aims and methods.

Formal science

Formal science is involved in the study of formal systems. It includes mathematics,[96][97] systems theory, and theoretical computer science. The formal sciences share similarities with the other two branches by relying on objective, careful, and systematic study of an area of knowledge. They are, however, different from the empirical sciences as they rely exclusively on deductive reasoning, without the need for empirical evidence, to verify their abstract concepts.[21][98][92] The formal sciences are therefore a priori disciplines and because of this, there is disagreement on whether they actually constitute a science.[19][20] Nevertheless, the formal sciences play an important role in the empirical sciences. Calculus, for example, was initially invented to understand motion in physics.[99] Natural and social sciences that rely heavily on mathematical applications include mathematical physics, mathematical chemistry, mathematical biology, mathematical finance, and mathematical economics.

References

  1. Harper, Douglas. “science”. Online Etymology Dictionary. Retrieved September 20, 2014.
  2. Wilson, E.O. (1999). “The natural sciences”. Consilience: The Unity of Knowledge (Reprint ed.). New York, New York: Vintage. pp. 49–71. ISBN978-0-679-76867-8.
  3. “… modern science is a discovery as well as an invention. It was a discovery that nature generally acts regularly enough to be described by laws and even by mathematics; and required invention to devise the techniques, abstractions, apparatus, and organization for exhibiting the regularities and securing their law-like descriptions.”— p.vii Heilbron, J.L. (editor-in-chief)(2003). “Preface”. The Oxford Companion to the History of Modern Science. New York: Oxford University Press. pp. vii–X. ISBN 978-0-19-511229-0.
  4. “science”. Merriam-Webster Online Dictionary. Merriam-Webster, Inc. Retrieved October 16, 2011. 3 a:knowledge or a system of knowledge covering general truths or the operation of general laws especially as obtained and tested through scientific method b: such knowledge or such a system of knowledge concerned with the physical world and its phenomena.
  5. “The historian … requires a very broad definition of “science” – one that … will help us to understand the modern scientific enterprise. We need to be broad and inclusive, rather than narrow and exclusive … and we should expect that the farther back we go [in time] the broader we will need to be.”  p.3—Lindberg, David C. (2007). “Science before the Greeks”. The beginnings of Western science: the European Scientific tradition in philosophical, religious, and institutional context(Second ed.). Chicago, Illinois: University of Chicago Press. pp. 1–27. ISBN978-0-226-48205-7.
  6. Grant, Edward (2007). “Ancient Egypt to Plato”. A History of Natural Philosophy: From the Ancient World to the Nineteenth Century (First ed.). New York, New York: Cambridge University Press. pp. 1–26. ISBN978-052-1-68957-1.
  7. Lindberg, David C. (2007). “The revival of learning in the West”. The beginnings of Western science: the European Scientific tradition in philosophical, religious, and institutional context (Second ed.). Chicago, Illinois: University of Chicago Press. pp. 193–224. ISBN978-0-226-48205-7.
  8. Lindberg, David C. (2007). “Islamic science”. The beginnings of Western science: the European Scientific tradition in philosophical, religious, and institutional context (Second ed.). Chicago, Illinois: University of Chicago Press. pp. 163–92. ISBN978-0-226-48205-7.
  9. Lindberg, David C. (2007). “The recovery and assimilation of Greek and Islamic science”. The beginnings of Western science: the European Scientific tradition in philosophical, religious, and institutional context (2nd ed.). Chicago, Illinois: University of Chicago Press. pp. 225–53. ISBN978-0-226-48205-7.
  10. Principe, Lawrence M. (2011). “Introduction”. Scientific Revolution: A Very Short Introduction (First ed.). New York, New York: Oxford University Press. pp. 1–3. ISBN978-0-199-56741-6.
  11. Lindberg, David C. (1990). “Conceptions of the Scientific Revolution from Baker to Butterfield: A preliminary sketch”. In David C. Lindberg; Robert S. Westman (eds.). Reappraisals of the Scientific Revolution (First ed.). Chicago, Illinois: Cambridge University Press. pp. 1–26. ISBN978-0-521-34262-9.
  12. Lindberg, David C. (2007). “The legacy of ancient and medieval science”. The beginnings of Western science: the European Scientific tradition in philosophical, religious, and institutional context (2nd ed.). Chicago, Illinois: University of Chicago Press. pp. 357–368. ISBN978-0-226-48205-7.
  13. Del Soldato, Eva (2016). Zalta, Edward N. (ed.). The Stanford Encyclopedia of Philosophy(Fall 2016 ed.). Metaphysics Research Lab, Stanford University.
  14. Grant, Edward (2007). “Transformation of medieval natural philosophy from the early period modern period to the end of the nineteenth century”. A History of Natural Philosophy: From the Ancient World to the Nineteenth Century (First ed.). New York, New York: Cambridge University Press. pp. 274–322. ISBN978-052-1-68957-1.
  15. Cahan, David, ed. (2003). From Natural Philosophy to the Sciences: Writing the History of Nineteenth-Century Science. Chicago, Illinois: University of Chicago Press. ISBN978-0-226-08928-7.
  16. The Oxford English Dictionarydates the origin of the word “scientist” to 1834.
  17. Lightman, Bernard (2011). “13. Science and the Public”. In Shank, Michael; Numbers, Ronald; Harrison, Peter (eds.). Wrestling with Nature : From Omens to Science. Chicago: University of Chicago Press. p. 367. ISBN978-0226317830.
  18. Harrison, Peter(2015). The Territories of Science and Religion. Chicago: University of Chicago Press. pp. 164–165. ISBN 9780226184517. The changing character of those engaged in scientific endeavors was matched by a new nomenclature for their endeavors. The most conspicuous marker of this change was the replacement of “natural philosophy” by “natural science”. In 1800 few had spoken of the “natural sciences” but by 1880, this expression had overtaken the traditional label “natural philosophy”. The persistence of “natural philosophy” in the twentieth century is owing largely to historical references to a past practice (see figure 11). As should now be apparent, this was not simply the substitution of one term by another, but involved the jettisoning of a range of personal qualities relating to the conduct of philosophy and the living of the philosophical life.
  19. Bishop, Alan (1991). “Environmental activities and mathematical culture”. Mathematical Enculturation: A Cultural Perspective on Mathematics Education. Norwell, Massachusetts: Kluwer Academic Publishers. pp. 20–59. ISBN978-0-792-31270-3.
  20. Bunge, Mario (1998). “The Scientific Approach”. Philosophy of Science: Volume 1, From Problem to Theory. 1(revised ed.). New York, New York: Routledge. pp. 3–50. ISBN978-0-765-80413-6.
  21. Fetzer, James H. (2013). “Computer reliability and public policy: Limits of knowledge of computer-based systems”. Computers and Cognition: Why Minds are not Machines (1st ed.). Newcastle, United Kingdom: Kluwer Academic Publishers. pp. 271–308. ISBN978-1-443-81946-6.
  22. Fischer, M.R.; Fabry, G (2014). “Thinking and acting scientifically: Indispensable basis of medical education”. GMS Zeitschrift für Medizinische Ausbildung. 31(2): Doc24. doi:3205/zma000916. PMC 4027809. PMID 24872859.
  23. Abraham, Reem Rachel (2004). “Clinically oriented physiology teaching: strategy for developing critical-thinking skills in undergraduate medical students”. Advances in Physiology Education. 28(3): 102–04. doi:1152/advan.00001.2004. PMID 15319191.
  24. Sinclair, Marius. “On the Differences between the Engineering and Scientific Methods”. The International Journal of Engineering Education.
  25. “Engineering Technology :: Engineering Technology :: Purdue School of Engineering and Technology, IUPUI”. www.engr.iupui.edu. Retrieved September 7, 2018.
  26. Grant, Edward (January 1, 1997). “History of Science: When Did Modern Science Begin?”. The American Scholar. 66(1): 105–113. JSTOR 41212592.
  27. Pingree, David(December 1992). “Hellenophilia versus the History of Science”. Isis. 83 (4): 554–63. Bibcode:..83..554P. doi:10.1086/356288. JSTOR 234257.
  28. Sima Qian(司馬遷, d. 86 BCE) in his Records of the Grand Historian (太史公書) covering some 2500 years of Chinese history, records Sunshu Ao (孫叔敖, fl. c. 630–595 BCE – Zhou dynasty), the first known hydraulic engineer of China, cited in (Joseph Needham et al. (1971) Science and Civilisation in China 3 p. 271) as having built a reservoir which has lasted to this day.
  29. Rochberg, Francesca (2011). “Ch.1 Natural Knowledge in Ancient Mesopotamia”. In Shank, Michael; Numbers, Ronald; Harrison, Peter (eds.). Wrestling with Nature : From Omens to Science. Chicago: University of Chicago Press. p. 9. ISBN978-0226317830.
  30. McIntosh, Jane R. (2005). Ancient Mesopotamia: New Perspectives. Santa Barbara, California, Denver, Colorado, and Oxford, England: ABC-CLIO. pp. 273–76. ISBN978-1-57607-966-9.
  31. Aaboe (May 2, 1974). “Scientific Astronomy in Antiquity”. Philosophical Transactions of the Royal Society. 276(1257): 21–42. Bibcode:1974RSPTA.276…21A. doi:10.1098/rsta.1974.0007. JSTOR 74272.
  32. R D. Biggs (2005). “Medicine, Surgery, and Public Health in Ancient Mesopotamia”. Journal of Assyrian Academic Studies. 19(1): 7–18.
  33. Lehoux, Daryn (2011). “2. Natural Knowledge in the Classical World”. In Shank, Michael; Numbers, Ronald; Harrison, Peter (eds.). Wrestling with Nature : From Omens to Science. Chicago: University of Chicago Press. p. 39. ISBN978-0226317830.
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Social Science: meaning, nature and scope

Social science is the branch of science devoted to the study of human societies and the relationships among individuals within those societies. The term was formerly used to refer to the field of sociology, the original “science of society”, established in the 19th century. In addition to sociology, it now encompasses a wide array of academic disciplines, including anthropology, archaeology, economics, human geography, linguistics, management science, media studies, musicology, political science, psychology, and social history.

Positivist social scientists use methods resembling those of the natural sciences as tools for understanding society, and so define science in its stricter modern sense. Interpretivist social scientists, by contrast, may use social critique or symbolic interpretation rather than constructing empirically falsifiable theories, and thus treat science in its broader sense. In modern academic practice, researchers are often eclectic, using multiple methodologies (for instance, by combining both quantitative and qualitative research). The term “social research” has also acquired a degree of autonomy as practitioners from various disciplines share in its aims and methods.

History

The history of the social sciences begins in the Age of Enlightenment after 1650,[1] which saw a revolution within natural philosophy, changing the basic framework by which individuals understood what was “scientific”. Social sciences came forth from the moral philosophy of the time and were influenced by the Age of Revolutions, such as the Industrial Revolution and the French Revolution.[2] The social sciences developed from the sciences (experimental and applied), or the systematic knowledge-bases or prescriptive practices, relating to the social improvement of a group of interacting entities.[3][4]

The beginnings of the social sciences in the 18th century are reflected in the grand encyclopedia of Diderot, with articles from Jean-Jacques Rousseau and other pioneers. The growth of the social sciences is also reflected in other specialized encyclopedias. The modern period saw “social science” first used as a distinct conceptual field.[5] Social science was influenced by positivism,[2] focusing on knowledge based on actual positive sense experience and avoiding the negative; metaphysical speculation was avoided. Auguste Comte used the term “science sociale” to describe the field, taken from the ideas of Charles Fourier; Comte also referred to the field as social physics.[2][6]

Following this period, five paths of development sprang forth in the social sciences, influenced by Comte in other fields.[2] One route that was taken was the rise of social research. Large statistical surveys were undertaken in various parts of the United States and Europe. Another route undertaken was initiated by Émile Durkheim, studying “social facts”, and Vilfredo Pareto, opening metatheoretical ideas and individual theories. A third means developed, arising from the methodological dichotomy present, in which social phenomena were identified with and understood; this was championed by figures such as Max Weber. The fourth route taken, based in economics, was developed and furthered economic knowledge as a hard science. The last path was the correlation of knowledge and social values; the antipositivism and verstehen sociology of Max Weber firmly demanded this distinction. In this route, theory (description) and prescription were non-overlapping formal discussions of a subject.

Around the start of the 20th century, Enlightenment philosophy was challenged in various quarters. After the use of classical theories since the end of the scientific revolution, various fields substituted mathematics studies for experimental studies and examining equations to build a theoretical structure. The development of social science subfields became very quantitative in methodology. The interdisciplinary and cross-disciplinary nature of scientific inquiry into human behaviour, social and environmental factors affecting it, made many of the natural sciences interested in some aspects of social science methodology.[7] Examples of boundary blurring include emerging disciplines like social research of medicine, sociobiology, neuropsychology, bioeconomics and the history and sociology of science. Increasingly, quantitative research and qualitative methods are being integrated in the study of human action and its implications and consequences. In the first half of the 20th century, statistics became a free-standing discipline of applied mathematics. Statistical methods were used confidently.

In the contemporary period, Karl Popper and Talcott Parsons influenced the furtherance of the social sciences.[2] Researchers continue to search for a unified consensus on what methodology might have the power and refinement to connect a proposed “grand theory” with the various midrange theories that, with considerable success, continue to provide usable frameworks for massive, growing data banks; for more, see consilience. The social sciences will for the foreseeable future be composed of different zones in the research of, and sometime distinct in approach toward, the field.[2]

The term “social science” may refer either to the specific sciences of society established by thinkers such as Comte, Durkheim, Marx, and Weber, or more generally to all disciplines outside of “noble science” and arts. By the late 19th century, the academic social sciences were constituted of five fields: jurisprudence and amendment of the law, education, health, economy and trade, and art.[3]

Around the start of the 21st century, the expanding domain of economics in the social sciences has been described as economic imperialism.[8]

Branches

The social science disciplines are branches of knowledge taught and researched at the college or university level. Social science disciplines are defined and recognized by the academic journals in which research is published, and the learned social science societies and academic departments or faculties to which their practitioners belong. Social science fields of study usually have several sub-disciplines or branches, and the distinguishing lines between these are often both arbitrary and ambiguous.

Anthropology

Anthropology is the holistic “science of man”, a science of the totality of human existence. The discipline deals with the integration of different aspects of the social sciences, humanities, and human biology. In the twentieth century, academic disciplines have often been institutionally divided into three broad domains. The natural sciences seek to derive general laws through reproducible and verifiable experiments. The humanities generally study local traditions, through their history, literature, music, and arts, with an emphasis on understanding particular individuals, events, or eras. The social sciences have generally attempted to develop scientific methods to understand social phenomena in a generalizable way, though usually with methods distinct from those of the natural sciences.

The anthropological social sciences often develop nuanced descriptions rather than the general laws derived in physics or chemistry, or they may explain individual cases through more general principles, as in many fields of psychology. Anthropology (like some fields of history) does not easily fit into one of these categories, and different branches of anthropology draw on one or more of these domains.[9] Within the United States, anthropology is divided into four sub-fields: archaeology, physical or biological anthropology, anthropological linguistics, and cultural anthropology. It is an area that is offered at most undergraduate institutions. The word anthropos (ἄνθρωπος) in Ancient Greek means “human being” or “person”. Eric Wolf described sociocultural anthropology as “the most scientific of the humanities, and the most humanistic of the sciences”.

The goal of anthropology is to provide a holistic account of humans and human nature. This means that, though anthropologists generally specialize in only one sub-field, they always keep in mind the biological, linguistic, historic and cultural aspects of any problem. Since anthropology arose as a science in Western societies that were complex and industrial, a major trend within anthropology has been a methodological drive to study peoples in societies with more simple social organization, sometimes called “primitive” in anthropological literature, but without any connotation of “inferior”.[10] Today, anthropologists use terms such as “less complex” societies or refer to specific modes of subsistence or production, such as “pastoralist” or “forager” or “horticulturalist” to refer to humans living in non-industrial, non-Western cultures, such people or folk (ethnos) remaining of great interest within anthropology.

The quest for holism leads most anthropologists to study a people in detail, using biogenetic, archaeological, and linguistic data alongside direct observation of contemporary customs.[11] In the 1990s and 2000s, calls for clarification of what constitutes a culture, of how an observer knows where his or her own culture ends and another begins, and other crucial topics in writing anthropology were heard. It is possible to view all human cultures as part of one large, evolving global culture. These dynamic relationships, between what can be observed on the ground, as opposed to what can be observed by compiling many local observations remain fundamental in any kind of anthropology, whether cultural, biological, linguistic or archaeological.[12]

Communication studies

Communication studies deals with processes of human communication, commonly defined as the sharing of symbols to create meaning. The discipline encompasses a range of topics, from face-to-face conversation to mass media outlets such as television broadcasting. Communication studies also examines how messages are interpreted through the political, cultural, economic, and social dimensions of their contexts. Communication is institutionalized under many different names at different universities, including “communication”, “communication studies”, “speech communication”, “rhetorical studies”, “communication science”, “media studies”, “communication arts”, “mass communication”, “media ecology”, and “communication and media science”.

Communication studies integrates aspects of both social sciences and the humanities. As a social science, the discipline often overlaps with sociology, psychology, anthropology, biology, political science, economics, and public policy, among others. From a humanities perspective, communication is concerned with rhetoric and persuasion (traditional graduate programs in communication studies trace their history to the rhetoricians of Ancient Greece). The field applies to outside disciplines as well, including engineering, architecture, mathematics, and information science.

Economics

Economics is a social science that seeks to analyze and describe the production, distribution, and consumption of wealth.[13] The word “economics” is from the Ancient Greek οἶκος oikos, “family, household, estate”, and νόμος nomos, “custom, law”, and hence means “household management” or “management of the state”. An economist is a person using economic concepts and data in the course of employment, or someone who has earned a degree in the subject. The classic brief definition of economics, set out by Lionel Robbins in 1932, is “the science which studies human behavior as a relation between scarce means having alternative uses”. Without scarcity and alternative uses, there is no economic problem. Briefer yet is “the study of how people seek to satisfy needs and wants” and “the study of the financial aspects of human behavior”.

Buyers bargain for good prices while sellers put forth their best front in Chichicastenango Market, Guatemala.
Economics has two broad branches: microeconomics, where the unit of analysis is the individual agent, such as a household or firm, and macroeconomics, where the unit of analysis is an economy as a whole. Another division of the subject distinguishes positive economics, which seeks to predict and explain economic phenomena, from normative economics, which orders choices and actions by some criterion; such orderings necessarily involve subjective value judgments. Since the early part of the 20th century, economics has focused largely on measurable quantities, employing both theoretical models and empirical analysis. Quantitative models, however, can be traced as far back as the physiocratic school. Economic reasoning has been increasingly applied in recent decades to other social situations such as politics, law, psychology, history, religion, marriage and family life, and other social interactions. This paradigm crucially assumes (1) that resources are scarce because they are not sufficient to satisfy all wants, and (2) that “economic value” is willingness to pay as revealed for instance by market (arms’ length) transactions. Rival heterodox schools of thought, such as institutional economics, green economics, Marxist economics, and economic sociology, make other grounding assumptions. For example, Marxist economics assumes that economics primarily deals with the investigation of exchange value, of which human labour is the source.

The expanding domain of economics in the social sciences has been described as economic imperialism.[8][14]

Education

Education encompasses teaching and learning specific skills, and also something less tangible but more profound: the imparting of knowledge, positive judgement and well-developed wisdom. Education has as one of its fundamental aspects the imparting of culture from generation to generation (see socialization). To educate means ‘to draw out’, from the Latin educare, or to facilitate the realization of an individual’s potential and talents. It is an application of pedagogy, a body of theoretical and applied research relating to teaching and learning and draws on many disciplines such as psychology, philosophy, computer science, linguistics, neuroscience, sociology and anthropology.[15]

The education of an individual human begins at birth and continues throughout life. (Some believe that education begins even before birth, as evidenced by some parents’ playing music or reading to the baby in the womb in the hope it will influence the child’s development.) For some, the struggles and triumphs of daily life provide far more instruction than does formal schooling (thus Mark Twain’s admonition to “never let school interfere with your education”).

Geography

Geography as a discipline can be split broadly into two main sub fields: human geography and physical geography. The former focuses largely on the built environment and how space is created, viewed and managed by humans as well as the influence humans have on the space they occupy. This may involve cultural geography, transportation, health, military operations, and cities. The latter examines the natural environment and how the climate, vegetation and life, soil, oceans, water and landforms are produced and interact.[16] Physical geography examines phenomena related to the measurement of earth. As a result of the two subfields using different approaches a third field has emerged, which is environmental geography. Environmental geography combines physical and human geography and looks at the interactions between the environment and humans.[17] Other branches of geography include social geography, regional geography, and geomatics.

Geographers attempt to understand the Earth in terms of physical and spatial relationships. The first geographers focused on the science of mapmaking and finding ways to precisely project the surface of the earth. In this sense, geography bridges some gaps between the natural sciences and social sciences. Historical geography is often taught in a college in a unified Department of Geography.

Modern geography is an all-encompassing discipline, closely related to GISc, that seeks to understand humanity and its natural environment. The fields of urban planning, regional science, and planetology are closely related to geography. Practitioners of geography use many technologies and methods to collect data such as GIS, remote sensing, aerial photography, statistics, and global positioning systems (GPS).

History

History is the continuous, systematic narrative and research into past human events as interpreted through historiographical paradigms or theories.

History has a base in both the social sciences and the humanities. In the United States the National Endowment for the Humanities includes history in its definition of humanities (as it does for applied linguistics).[18] However, the National Research Council classifies history as a social science.[19] The historical method comprises the techniques and guidelines by which historians use primary sources and other evidence to research and then to write history. The Social Science History Association, formed in 1976, brings together scholars from numerous disciplines interested in social history.[20]

Law

The social science of law, jurisprudence, in common parlance, means a rule that (unlike a rule of ethics) is capable of enforcement through institutions.[21] However, many laws are based on norms accepted by a community and thus have an ethical foundation. The study of law crosses the boundaries between the social sciences and humanities, depending on one’s view of research into its objectives and effects. Law is not always enforceable, especially in the international relations context. It has been defined as a “system of rules”,[22] as an “interpretive concept”[23] to achieve justice, as an “authority”[24] to mediate people’s interests, and even as “the command of a sovereign, backed by the threat of a sanction”.[25] However one likes to think of law, it is a completely central social institution. Legal policy incorporates the practical manifestation of thinking from almost every social science and the humanities. Laws are politics, because politicians create them. Law is philosophy, because moral and ethical persuasions shape their ideas. Law tells many of history’s stories, because statutes, case law and codifications build up over time. And law is economics, because any rule about contract, tort, property law, labour law, company law and many more can have long-lasting effects on the distribution of wealth. The noun law derives from the late Old English lagu, meaning something laid down or fixed[26] and the adjective legal comes from the Latin word lex.[27]

Linguistics

Linguistics investigates the cognitive and social aspects of human language. The field is divided into areas that focus on aspects of the linguistic signal, such as syntax (the study of the rules that govern the structure of sentences), semantics (the study of meaning), morphology (the study of the structure of words), phonetics (the study of speech sounds) and phonology (the study of the abstract sound system of a particular language); however, work in areas like evolutionary linguistics (the study of the origins and evolution of language) and psycholinguistics (the study of psychological factors in human language) cut across these divisions.

The overwhelming majority of modern research in linguistics takes a predominantly synchronic perspective (focusing on language at a particular point in time), and a great deal of it—partly owing to the influence of Noam Chomsky—aims at formulating theories of the cognitive processing of language. However, language does not exist in a vacuum, or only in the brain, and approaches like contact linguistics, creole studies, discourse analysis, social interactional linguistics, and sociolinguistics explore language in its social context. Sociolinguistics often makes use of traditional quantitative analysis and statistics in investigating the frequency of features, while some disciplines, like contact linguistics, focus on qualitative analysis. While certain areas of linguistics can thus be understood as clearly falling within the social sciences, other areas, like acoustic phonetics and neurolinguistics, draw on the natural sciences. Linguistics draws only secondarily on the humanities, which played a rather greater role in linguistic inquiry in the 19th and early 20th centuries. Ferdinand Saussure is considered the father of modern linguistics.

Political science

Political science is an academic and research discipline that deals with the theory and practice of politics and the description and analysis of political systems and political behaviour. Fields and subfields of political science include political economy, political theory and philosophy, civics and comparative politics, theory of direct democracy, apolitical governance, participatory direct democracy, national systems, cross-national political analysis, political development, international relations, foreign policy, international law, politics, public administration, administrative behaviour, public law, judicial behaviour, and public policy. Political science also studies power in international relations and the theory of great powers and superpowers.

Political science is methodologically diverse, although recent years have witnessed an upsurge in the use of the scientific method,[29][page needed] that is, the proliferation of formal-deductive model building and quantitative hypothesis testing. Approaches to the discipline include rational choice, classical political philosophy, interpretivism, structuralism, and behaviouralism, realism, pluralism, and institutionalism. Political science, as one of the social sciences, uses methods and techniques that relate to the kinds of inquiries sought: primary sources such as historical documents, interviews, and official records, as well as secondary sources such as scholarly articles are used in building and testing theories. Empirical methods include survey research, statistical analysis or econometrics, case studies, experiments, and model building. Herbert Baxter Adams is credited with coining the phrase “political science” while teaching history at Johns Hopkins University.

Psychology

Psychology is an academic and applied field involving the study of behaviour and mental processes. Psychology also refers to the application of such knowledge to various spheres of human activity, including problems of individuals’ daily lives and the treatment of mental illness. The word psychology comes from the Ancient Greek ψυχή psyche (“soul”, “mind”) and logy (“study”).

Psychology differs from anthropology, economics, political science, and sociology in seeking to capture explanatory generalizations about the mental function and overt behaviour of individuals, while the other disciplines focus on creating descriptive generalizations about the functioning of social groups or situation-specific human behaviour. In practice, however, there is quite a lot of cross-fertilization that takes place among the various fields. Psychology differs from biology and neuroscience in that it is primarily concerned with the interaction of mental processes and behaviour, and of the overall processes of a system, and not simply the biological or neural processes themselves, though the subfield of neuropsychology combines the study of the actual neural processes with the study of the mental effects they have subjectively produced. Many people associate psychology with clinical psychology, which focuses on assessment and treatment of problems in living and psychopathology. In reality, psychology has myriad specialties including social psychology, developmental psychology, cognitive psychology, educational psychology, industrial-organizational psychology, mathematical psychology, neuropsychology, and quantitative analysis of behaviour.

Psychology is a very broad science that is rarely tackled as a whole, major block. Although some subfields encompass a natural science base and a social science application, others can be clearly distinguished as having little to do with the social sciences or having a lot to do with the social sciences. For example, biological psychology is considered a natural science with a social scientific application (as is clinical medicine), social and occupational psychology are, generally speaking, purely social sciences, whereas neuropsychology is a natural science that lacks application out of the scientific tradition entirely. In British universities, emphasis on what tenet of psychology a student has studied and/or concentrated is communicated through the degree conferred: B.Psy. indicates a balance between natural and social sciences, B.Sc. indicates a strong (or entire) scientific concentration, whereas a B.A. underlines a majority of social science credits. This is not always necessarily the case however, and in many UK institutions students studying the B.Psy, B.Sc, and B.A. follow the same curriculum as outlined by The British Psychological Society and have the same options of specialism open to them regardless of whether they choose a balance, a heavy science basis, or heavy social science basis to their degree. If they applied to read the B.A. for example, but specialized in heavily science-based modules, then they will still generally be awarded the B.A.

Sociology

Sociology is the systematic study of society, individuals’ relationship to their societies, the consequences of difference, and other aspects of human social action.[30] The meaning of the word comes from the suffix “-logy”, which means “study of”, derived from Ancient Greek, and the stem “soci-“, which is from the Latin word socius, meaning “companion”, or society in general.

Auguste Comte (1798–1857) coined the term, Sociology, as a way to apply natural science principles and techniques to the social world in 1838.[31][32] Comte endeavoured to unify history, psychology and economics through the descriptive understanding of the social realm. He proposed that social ills could be remedied through sociological positivism, an epistemological approach outlined in The Course in Positive Philosophy [1830–1842] and A General View of Positivism (1844). Though Comte is generally regarded as the “Father of Sociology”, the discipline was formally established by another French thinker, Émile Durkheim (1858–1917), who developed positivism as a foundation to practical social research. Durkheim set up the first European department of sociology at the University of Bordeaux in 1895, publishing his Rules of the Sociological Method. In 1896, he established the journal L’Année Sociologique. Durkheim’s seminal monograph, Suicide (1897), a case study of suicide rates among Catholic and Protestant populations, distinguished sociological analysis from psychology or philosophy.[33]

Karl Marx rejected Comte’s positivism but nevertheless aimed to establish a science of society based on historical materialism, becoming recognized as a founding figure of sociology posthumously as the term gained broader meaning. Around the start of the 20th century, the first wave of German sociologists, including Max Weber and Georg Simmel, developed sociological antipositivism. The field may be broadly recognized as an amalgam of three modes of social thought in particular: Durkheimian positivism and structural functionalism; Marxist historical materialism and conflict theory; and Weberian antipositivism and verstehen analysis. American sociology broadly arose on a separate trajectory, with little Marxist influence, an emphasis on rigorous experimental methodology, and a closer association with pragmatism and social psychology. In the 1920s, the Chicago school developed symbolic interactionism. Meanwhile, in the 1930s, the Frankfurt School pioneered the idea of critical theory, an interdisciplinary form of Marxist sociology drawing upon thinkers as diverse as Sigmund Freud and Friedrich Nietzsche. Critical theory would take on something of a life of its own after World War II, influencing literary criticism and the Birmingham School establishment of cultural studies.

Sociology evolved as an academic response to the challenges of modernity, such as industrialization, urbanization, secularization, and a perceived process of enveloping rationalization.[34] The field generally concerns the social rules and processes that bind and separate people not only as individuals, but as members of associations, groups, communities and institutions, and includes the examination of the organization and development of human social life. The sociological field of interest ranges from the analysis of short contacts between anonymous individuals on the street to the study of global social processes. In the terms of sociologists Peter L. Berger and Thomas Luckmann, social scientists seek an understanding of the Social Construction of Reality. Most sociologists work in one or more subfields. One useful way to describe the discipline is as a cluster of sub-fields that examine different dimensions of society. For example, social stratification studies inequality and class structure; demography studies changes in a population size or type; criminology examines criminal behaviour and deviance; and political sociology studies the interaction between society and state.

Since its inception, sociological epistemologies, methods, and frames of enquiry, have significantly expanded and diverged.[35] Sociologists use a diversity of research methods, collect both quantitative and qualitative data, draw upon empirical techniques, and engage critical theory.[32] Common modern methods include case studies, historical research, interviewing, participant observation, social network analysis, survey research, statistical analysis, and model building, among other approaches. Since the late 1970s, many sociologists have tried to make the discipline useful for purposes beyond the academy. The results of sociological research aid educators, lawmakers, administrators, developers, and others interested in resolving social problems and formulating public policy, through subdisciplinary areas such as evaluation research, methodological assessment, and public sociology.

In the early 1970s, women sociologists began to question sociological paradigms and the invisibility of women in sociological studies, analysis, and courses.[36] In 1969, feminist sociologists challenged the discipline’s androcentrism at the American Sociological Association’s annual conference.[37] This led to the founding of the organization Sociologists for Women in Society, and, eventually, a new sociology journal, Gender & Society. Today, the sociology of gender is considered to be one of the most prominent sub-fields in the discipline.

New sociological sub-fields continue to appear — such as community studies, computational sociology, environmental sociology, network analysis, actor-network theory, gender studies, and a growing list, many of which are cross-disciplinary in nature.[38]

Methodology

Social research

The origin of the survey can be traced back at least early as the Domesday Book in 1086,[41][42] while some scholars pinpoint the origin of demography to 1663 with the publication of John Graunt’s Natural and Political Observations upon the Bills of Mortality.[43] Social research began most intentionally, however, with the positivist philosophy of science in the 19th century.

In contemporary usage, “social research” is a relatively autonomous term, encompassing the work of practitioners from various disciplines that share in its aims and methods. Social scientists employ a range of methods in order to analyse a vast breadth of social phenomena; from census survey data derived from millions of individuals, to the in-depth analysis of a single agent’s social experiences; from monitoring what is happening on contemporary streets, to the investigation of ancient historical documents. The methods originally rooted in classical sociology and statistical mathematics have formed the basis for research in other disciplines, such as political science, media studies, and marketing and market research.

Social research methods may be divided into two broad schools:

Quantitative designs approach social phenomena through quantifiable evidence, and often rely on statistical analysis of many cases (or across intentionally designed treatments in an experiment) to create valid and reliable general claims.
Qualitative designs emphasize understanding of social phenomena through direct observation, communication with participants, or analysis of texts, and may stress contextual and subjective accuracy over generality.
Social scientists will commonly combine quantitative and qualitative approaches as part of a multi-strategy design. Questionnaires, field-based data collection, archival database information and laboratory-based data collections are some of the measurement techniques used. It is noted the importance of measurement and analysis, focusing on the (difficult to achieve) goal of objective research or statistical hypothesis testing. A mathematical model uses mathematical language to describe a system. The process of developing a mathematical model is termed ‘mathematical modelling’ (also modeling). Eykhoff (1974) defined a mathematical model as ‘a representation of the essential aspects of an existing system (or a system to be constructed) that presents knowledge of that system in usable form’.[44] Mathematical models can take many forms, including but not limited to dynamical systems, statistical models, differential equations, or game theoretic models.

These and other types of models can overlap, with a given model involving a variety of abstract structures. The system is a set of interacting or interdependent entities, real or abstract, forming an integrated whole. The concept of an integrated whole can also be stated in terms of a system embodying a set of relationships that are differentiated from relationships of the set to other elements, and from relationships between an element of the set and elements not a part of the relational regime. A dynamical system modeled as a mathematical formalization has a fixed “rule” that describes the time dependence of a point’s position in its ambient space. Small changes in the state of the system correspond to small changes in the numbers. The evolution rule of the dynamical system is a fixed rule that describes what future states follow from the current state. The rule is deterministic: for a given time interval only one future state follows from the current state.

Social scientists often conduct Program Evaluation, which is a systematic method for collecting, analyzing, and using information to answer questions about projects, policies and programs,[45] particularly about their effectiveness and efficiency. In both the public and private sectors, stakeholders often want to know whether the programs they are funding, implementing, voting for, receiving or objecting to are producing the intended effect. While program evaluation first focuses around this definition, important considerations often include how much the program costs per participant, how the program could be improved, whether the program is worthwhile, whether there are better alternatives, if there are unintended outcomes, and whether the program goals are appropriate and useful.[46]

Theory

Other social scientists emphasize the subjective nature of research. These writers share social theory perspectives that include various types of the following:

  • Critical theory is the examination and critique of society and culture, drawing from knowledge across social sciences and humanities disciplines.
  • Dialectical materialism is the philosophy of Karl Marx, which he formulated by taking the dialectic of Hegel and joining it to the materialism of Feuerbach.
  • Feminist theory is the extension of feminism into theoretical, or philosophical discourse; it aims to understand the nature of gender inequality.
  • Marxist theories, such as revolutionary theory and class theory, cover work in philosophy that is strongly influenced by Karl Marx’s materialist approach to theory or is written by Marxists.
  • Phronetic social science is a theory and methodology for doing social science focusing on ethics and political power, based on a contemporary interpretation of Aristotelian phronesis.
  • Post-colonial theory is a reaction to the cultural legacy of colonialism.
  • Postmodernism refers to a point of departure for works of literature, drama, architecture, cinema, and design, as well as in marketing and business and in the interpretation of history, law, culture and religion in the late 20th century.
  • Rational choice theory is a framework for understanding and often formally modeling social and economic behaviour.
  • Social constructionism considers how social phenomena develop in social contexts.
  • Structuralism is an approach to the human sciences that attempts to analyze a specific field (for instance, mythology) as a complex system of interrelated parts.
  • Structural functionalism is a sociological paradigm that addresses what social functions various elements of the social system perform in regard to the entire system.

Other fringe social scientists delve in alternative nature of research. These writers share social theory perspectives that include various types of the following:

  • Intellectual critical-ism describes a sentiment of critique towards, or evaluation of, intellectuals and intellectual pursuits.
  • Scientific criticalism is a position critical of science and the scientific method.

Education and degrees

Most universities offer degrees in social science fields.[47] The Bachelor of Social Science is a degree targeted at the social sciences in particular. It is often more flexible and in-depth than other degrees that include social science subjects.[a]

In the United States, a university may offer a student who studies a social sciences field a Bachelor of Arts degree, particularly if the field is within one of the traditional liberal arts such as history, or a BSc: Bachelor of Science degree such as those given by the London School of Economics, as the social sciences constitute one of the two main branches of science (the other being the natural sciences). In addition, some institutions have degrees for a particular social science, such as the Bachelor of Economics degree, though such specialized degrees are relatively rare in the United States.

Graduate students may get a Master’s degree (Master of Arts, Master of Science or a field-specific degree such as Master of Public Administration) or Ph.D.

References

  1. Kuper, Adam (1996). The Social Science Encyclopedia. Taylor & Francis. ISBN978-0-415-10829-4.
  2. Kuper, A., and Kuper, J. (1985). The Social Science Encyclopaedia.
  3. Social sciences, Columbian Cyclopedia. (1897). Buffalo: Garretson, Cox & Company. p. 227.
  4. Peck, H.T., Peabody, S.H., and Richardson, C.F. (1897). The International Cyclopedia, A Compendium of Human Knowledge. Rev. with large additions. New York: Dodd, Mead and Company.
  5. William Thompson(1775–1833) (1824). An Inquiry into the Principles of the Distribution of Wealth Most Conducive to Human Happiness; applied to the Newly Proposed System of Voluntary Equality of Wealth.
  6. According to Comte, the social physicsfield was similar to that of natural sciences.
  7. Vessuri, H. (2002). “Ethical Challenges for the Social Sciences on the Threshold of the 21st Century”. Current Sociology. 50: 135–50. doi:1177/0011392102050001010.
  8. Lazear, E.P. (2000). “Economic Imperialism”. The Quarterly Journal of Economics. 115: 99–146. doi:1162/003355300554683.
  9. Wallerstein, I. (2003). “Anthropology, Sociology, and Other Dubious Disciplines”(PDF). Current Anthropology. 44 (4): 453–65. doi:1086/375868.
  10. Lowie, Robert (1924). Primitive Religion. Routledge and Sons.Tylor, Edward (1920). Primitive Culture. New York: J.P. Putnam’s Sons.Originally published 1871.
  11. Nanda, Serenaand Richard Warms. Culture Counts. Wadsworth. 2008. Chapter One
  12. Rosaldo, Renato. Culture and Truth: The remaking of social analysis. Beacon Press. 1993; Inda, John Xavier and Renato Rosaldo. The Anthropology of Globalization. Wiley-Blackwell. 2007
  13. economics – Britannica Online Encyclopedia
  14. Becker, Gary S.(1976). The Economic Approach to Human Behavior. Links to arrow-page viewable chapter. University of Chicago Press.
  15. An overview of education
  16. “What is geography?”. AAG Career Guide: Jobs in Geography and Related Geographical Sciences. Association of American Geographers. Archived from the originalon October 6, 2006. Retrieved October 9, 2006.
  17. Hayes-Bohanan, James. “What is Environmental Geography, Anyway?”. Retrieved October 9, 2006.
  18. “About NEH”. National Endowment for the Humanities.
  19. Research-Doctorate Programs in the United States: Continuity and Change
  20. See the SSHA website
  21. Robertson, Geoffrey(2006). Crimes Against Humanity. Penguin. p. 90. ISBN 978-0-14-102463-9.
  22. Hart, H.L.A.(1961). The Concept of Law. Oxford University Press. ISBN 978-0-19-876122-8.
  23. Dworkin, Ronald(1986). Law’s Empire. Harvard University Press. ISBN 978-0-674-51836-0.
  24. Raz, Joseph(1979). The Authority of Law. Oxford University Press. ISBN 978-0-19-956268-8.
  25. Austin, John(1831). The Providence of Jurisprudence Determined.
  26. see Etymonline Dictionary
  27. see Merriam-Webster’s Dictionary
  28. Ebenstein, Alan (2002). Introduction to Political Thinkers. Boston, Massachusetts: Wadsworth.
  29. Hindmoor, Andrew (August 8, 2006). Rational Choice. ISBN978-1-4039-3422-2.
  30. Witt, Jon (2018). SOC 218. McGraw-Hill. p. 2. ISBN978-1-259-70272-3.
  31. A Dictionary of Sociology, Article: Comte, Auguste
  32. Witt, Jon (2018). SOC 2018. McGraw-Hill. ISBN978-1-259-70272-3.
  33. Gianfranco Poggi (2000). Oxford: Oxford University Press. Chapter 1.
  34. Habermas, Jürgen, The Philosophical Discourse of Modernity: Modernity’s Consciousness of Time, Polity Press (1990), paperback, ISBN0-7456-0830-2, p. 2.
  35. Giddens, Anthony, Duneier, Mitchell, Applebaum, Richard. 2007. Introduction to Sociology. Sixth Edition.New York: W.W. Norton and Company. Chapter 1.
  36. Lorber, Judith (1994). Paradoxes of Gender. New Haven, CT: Yale University Press. ISBN978-0-300-06497-1.
  37. Laube, Heather; Hess, Bess B. (2001). “The Founding of SWS”. Sociologists for Women in Society. Retrieved February 5, 2018.
  38. Vuong, Quan-Hoang (2019). The Vietnamese Social Sciences at a Fork in the Road. De Gruyter. ISBN978-3110686081.
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  41. H. Halsey (2004), A history of sociology in Britain: science, literature, and society, p. 34
  42. Geoffrey Duncan Mitchell (1970), A new dictionary of sociology, p. 201
  43. Willcox, Walter (1938) The Founder of Statistics.
  44. Eykhoff, Pieter System Identification: Parameter and State Estimation, Wiley & Sons, (1974). ISBN0-471-24980-7
  45. Administration for Children and Families (2010) The Program Manager’s Guide to Evaluation. Chapter 2: What is program evaluation?.
  46. Shackman, Gene (February 11, 2018). “What Is Program Evaluation: A Beginner’s Guide”. The Global Social Change Research Project. SSRN3060080.
  47. Peterson’s (Firm : 2006– ). (2007). Peterson’s graduate programs in the humanities, arts, & social sciences, 2007. Lawrenceville, New Jersey: Peterson’s.

What is a Scientific Theory?

What is a Scientific Theory?

The University of California, Berkley, defines a theory as “a broad, natural explanation for a wide range of phenomena. Theories are concise, coherent, systematic, predictive, and broadly applicable, often integrating and generalizing many hypotheses.” A scientific theory is an explanation of an aspect of the natural world that can be repeatedly tested and verified in accordance with the scientific method, using accepted protocols of observation, measurement, and evaluation of results. Where possible, theories are tested under controlled conditions in an experiment.[1][2] In circumstances not amenable to experimental testing, theories are evaluated through principles of abductive reasoning. Established scientific theories have withstood rigorous scrutiny and embody scientific knowledge.[3]

The meaning of the term scientific theory (often contracted to theory for brevity) as used in the disciplines of science is significantly different from the common vernacular usage of theory.[4] In everyday speech, theory can imply an explanation that represents an unsubstantiated and speculative guess,[4] whereas in science it describes an explanation that has been tested and widely accepted as valid. These different usages are comparable to the opposing usages of prediction in science versus common speech, where it denotes a mere hope.

The strength of a scientific theory is related to the diversity of phenomena it can explain and its simplicity. As additional scientific evidence is gathered, a scientific theory may be modified and ultimately rejected if it cannot be made to fit the new findings; in such circumstances, a more accurate theory is then required. That does not mean that all theories can be fundamentally changed (for example, well established foundational scientific theories such as evolution, heliocentric theory, cell theory, theory of plate tectonics, germ theory of disease, etc.). In certain cases, the less-accurate unmodified scientific theory can still be treated as a theory if it is useful (due to its sheer simplicity) as an approximation under specific conditions. A case in point is Newton’s laws of motion, which can serve as an approximation to special relativity at velocities that are small relative to the speed of light.

Scientific theories are testable and make falsifiable predictions.[5] They describe the causes of a particular natural phenomenon and are used to explain and predict aspects of the physical universe or specific areas of inquiry (for example, electricity, chemistry, and astronomy). Scientists use theories to further scientific knowledge, as well as to facilitate advances in technology or medicine.

As with other forms of scientific knowledge, scientific theories are both deductive and inductive,[6] aiming for predictive and explanatory power.

The paleontologist Stephen Jay Gould wrote that “…facts and theories are different things, not rungs in a hierarchy of increasing certainty. Facts are the world’s data. Theories are structures of ideas that explain and interpret facts.”[7]

About theories

Theories and laws

Both scientific laws and scientific theories are produced from the scientific method through the formation and testing of hypotheses, and can predict the behavior of the natural world. Both are typically well-supported by observations and/or experimental evidence.[29] However, scientific laws are descriptive accounts of how nature will behave under certain conditions.[30] Scientific theories are broader in scope, and give overarching explanations of how nature works and why it exhibits certain characteristics. Theories are supported by evidence from many different sources, and may contain one or several laws.[31]

A common misconception is that scientific theories are rudimentary ideas that will eventually graduate into scientific laws when enough data and evidence have been accumulated. A theory does not change into a scientific law with the accumulation of new or better evidence. A theory will always remain a theory; a law will always remain a law.[29][32][33] Both theories and laws could potentially be falsified by countervailing evidence.[34]

Theories and laws are also distinct from hypotheses. Unlike hypotheses, theories and laws may be simply referred to as scientific fact.[35][36] However, in science, theories are different from facts even when they are well supported.[37] For example, evolution is both a theory and a fact.[4]

Theories as axioms

The logical positivists thought of scientific theories as statements in a formal language. First-order logic is an example of a formal language. The logical positivists envisaged a similar scientific language. In addition to scientific theories, the language also included observation sentences (“the sun rises in the east”), definitions, and mathematical statements. The phenomena explained by the theories, if they could not be directly observed by the senses (for example, atoms and radio waves), were treated as theoretical concepts. In this view, theories function as axioms: predicted observations are derived from the theories much like theorems are derived in Euclidean geometry. However, the predictions are then tested against reality to verify the theories, and the “axioms” can be revised as a direct result.

The phrase “the received view of theories” is used to describe this approach. Terms commonly associated with it are “linguistic” (because theories are components of a language) and “syntactic” (because a language has rules about how symbols can be strung together). Problems in defining this kind of language precisely, e.g., are objects seen in microscopes observed or are they theoretical objects, led to the effective demise of logical positivism in the 1970s.

Theories as models

The semantic view of theories, which identifies scientific theories with models rather than propositions, has replaced the received view as the dominant position in theory formulation in the philosophy of science.[38][39][40] A model is a logical framework intended to represent reality (a “model of reality”), similar to the way that a map is a graphical model that represents the territory of a city or country.[41][42]

Precession of the perihelion of Mercury (exaggerated). The deviation in Mercury’s position from the Newtonian prediction is about 43 arc-seconds (about two-thirds of 1/60 of a degree) per century.[43][44]

In this approach, theories are a specific category of models that fulfill the necessary criteria (see above). One can use language to describe a model; however, the theory is the model (or a collection of similar models), and not the description of the model. A model of the solar system, for example, might consist of abstract objects that represent the sun and the planets. These objects have associated properties, e.g., positions, velocities, and masses. The model parameters, e.g., Newton’s Law of Gravitation, determine how the positions and velocities change with time. This model can then be tested to see whether it accurately predicts future observations; astronomers can verify that the positions of the model’s objects over time match the actual positions of the planets. For most planets, the Newtonian model’s predictions are accurate; for Mercury, it is slightly inaccurate and the model of general relativity must be used instead.

The word “semantic” refers to the way that a model represents the real world. The representation (literally, “re-presentation”) describes particular aspects of a phenomenon or the manner of interaction among a set of phenomena. For instance, a scale model of a house or of a solar system is clearly not an actual house or an actual solar system; the aspects of an actual house or an actual solar system represented in a scale model are, only in certain limited ways, representative of the actual entity. A scale model of a house is not a house; but to someone who wants to learn about houses, analogous to a scientist who wants to understand reality, a sufficiently detailed scale model may suffice.

Differences between theory and model

Several commentators[45] have stated that the distinguishing characteristic of theories is that they are explanatory as well as descriptive, while models are only descriptive (although still predictive in a more limited sense). Philosopher Stephen Pepper also distinguished between theories and models, and said in 1948 that general models and theories are predicated on a “root” metaphor that constrains how scientists theorize and model a phenomenon and thus arrive at testable hypotheses.

Engineering practice makes a distinction between “mathematical models” and “physical models”; the cost of fabricating a physical model can be minimized by first creating a mathematical model using a computer software package, such as a computer aided design tool. The component parts are each themselves modelled, and the fabrication tolerances are specified. An exploded view drawing is used to lay out the fabrication sequence. Simulation packages for displaying each of the subassemblies allow the parts to be rotated, magnified, in realistic detail. Software packages for creating the bill of materials for construction allows subcontractors to specialize in assembly processes, which spreads the cost of manufacturing machinery among multiple customers. See: Computer-aided engineering, Computer-aided manufacturing, and 3D printing.

From philosophers of science

Karl Popper described the characteristics of a scientific theory as follows:[5]

  1. It is easy to obtain confirmations, or verifications, for nearly every theory—if we look for confirmations.
  2. Confirmations should count only if they are the result of risky predictions; that is to say, if, unenlightened by the theory in question, we should have expected an event which was incompatible with the theory—an event which would have refuted the theory.
  3. Every “good” scientific theory is a prohibition: it forbids certain things to happen. The more a theory forbids, the better it is.
  4. A theory which is not refutable by any conceivable event is non-scientific. Irrefutability is not a virtue of a theory (as people often think) but a vice.
  5. Every genuine test of a theory is an attempt to falsify it, or to refute it. Testability is falsifiability; but there are degrees of testability: some theories are more testable, more exposed to refutation, than others; they take, as it were, greater risks.
  6. Confirming evidence should not count except when it is the result of a genuine test of the theory; and this means that it can be presented as a serious but unsuccessful attempt to falsify the theory. (I now speak in such cases of “corroborating evidence”.)
  7. Some genuinely testable theories, when found to be false, might still be upheld by their admirers—for example by introducing post hoc (after the fact) some auxiliary hypothesis or assumption, or by reinterpreting the theory post hoc in such a way that it escapes refutation. Such a procedure is always possible, but it rescues the theory from refutation only at the price of destroying, or at least lowering, its scientific status, by tampering with evidence. The temptation to tamper can be minimized by first taking the time to write down the testing protocol before embarking on the scientific work.

Popper summarized these statements by saying that the central criterion of the scientific status of a theory is its “falsifiability, or refutability, or testability“.[5] Echoing this, Stephen Hawking states, “A theory is a good theory if it satisfies two requirements: It must accurately describe a large class of observations on the basis of a model that contains only a few arbitrary elements, and it must make definite predictions about the results of future observations.” He also discusses the “unprovable but falsifiable” nature of theories, which is a necessary consequence of inductive logic, and that “you can disprove a theory by finding even a single observation that disagrees with the predictions of the theory”.[47]

Several philosophers and historians of science have, however, argued that Popper’s definition of theory as a set of falsifiable statements is wrong[48] because, as Philip Kitcher has pointed out, if one took a strictly Popperian view of “theory”, observations of Uranus when first discovered in 1781 would have “falsified” Newton’s celestial mechanics. Rather, people suggested that another planet influenced Uranus’ orbit—and this prediction was indeed eventually confirmed.

Kitcher agrees with Popper that “There is surely something right in the idea that a science can succeed only if it can fail.”[49] He also says that scientific theories include statements that cannot be falsified, and that good theories must also be creative. He insists we view scientific theories as an “elaborate collection of statements”, some of which are not falsifiable, while others—those he calls “auxiliary hypotheses”, are.

According to Kitcher, good scientific theories must have three features:[49]

  1. Unity: “A science should be unified…. Good theories consist of just one problem-solving strategy, or a small family of problem-solving strategies, that can be applied to a wide range of problems.”
  2. Fecundity: “A great scientific theory, like Newton’s, opens up new areas of research…. Because a theory presents a new way of looking at the world, it can lead us to ask new questions, and so to embark on new and fruitful lines of inquiry…. Typically, a flourishing science is incomplete. At any time, it raises more questions than it can currently answer. But incompleteness is not vice. On the contrary, incompleteness is the mother of fecundity…. A good theory should be productive; it should raise new questions and presume those questions can be answered without giving up its problem-solving strategies.”
  3. Auxiliary hypotheses that are independently testable: “An auxiliary hypothesis ought to be testable independently of the particular problem it is introduced to solve, independently of the theory it is designed to save.” (For example, the evidence for the existence of Neptune is independent of the anomalies in Uranus’s orbit.)

Like other definitions of theories, including Popper’s, Kitcher makes it clear that a theory must include statements that have observational consequences. But, like the observation of irregularities in the orbit of Uranus, falsification is only one possible consequence of observation. The production of new hypotheses is another possible and equally important result.

Analogies and metaphors

The concept of a scientific theory has also been described using analogies and metaphors. For instance, the logical empiricist Carl Gustav Hempel likened the structure of a scientific theory to a “complex spatial network:”

Its terms are represented by the knots, while the threads connecting the latter correspond, in part, to the definitions and, in part, to the fundamental and derivative hypotheses included in the theory. The whole system floats, as it were, above the plane of observation and is anchored to it by the rules of interpretation. These might be viewed as strings which are not part of the network but link certain points of the latter with specific places in the plane of observation. By virtue of these interpretive connections, the network can function as a scientific theory: From certain observational data, we may ascend, via an interpretive string, to some point in the theoretical network, thence proceed, via definitions and hypotheses, to other points, from which another interpretive string permits a descent to the plane of observation.[50]

Michael Polanyi made an analogy between a theory and a map:

A theory is something other than myself. It may be set out on paper as a system of rules, and it is the more truly a theory the more completely it can be put down in such terms. Mathematical theory reaches the highest perfection in this respect. But even a geographical map fully embodies in itself a set of strict rules for finding one’s way through a region of otherwise uncharted experience. Indeed, all theory may be regarded as a kind of map extended over space and time.[51]

A scientific theory can also be thought of as a book that captures the fundamental information about the world, a book that must be researched, written, and shared. In 1623, Galileo Galilei wrote:

Philosophy [i.e. physics] is written in this grand book—I mean the universe—which stands continually open to our gaze, but it cannot be understood unless one first learns to comprehend the language and interpret the characters in which it is written. It is written in the language of mathematics, and its characters are triangles, circles, and other geometrical figures, without which it is humanly impossible to understand a single word of it; without these, one is wandering around in a dark labyrinth.[52]

The book metaphor could also be applied in the following passage, by the contemporary philosopher of science Ian Hacking:

I myself prefer an Argentine fantasy. God did not write a Book of Nature of the sort that the old Europeans imagined. He wrote a Borgesian library, each book of which is as brief as possible, yet each book of which is inconsistent with every other. No book is redundant. For every book there is some humanly accessible bit of Nature such that that book, and no other, makes possible the comprehension, prediction and influencing of what is going on…Leibniz said that God chose a world which maximized the variety of phenomena while choosing the simplest laws. Exactly so: but the best way to maximize phenomena and have simplest laws is to have the laws inconsistent with each other, each applying to this or that but none applying to all.[53]

In physics

In physics, the term theory is generally used for a mathematical framework—derived from a small set of basic postulates (usually symmetries—like equality of locations in space or in time, or identity of electrons, etc.)—that is capable of producing experimental predictions for a given category of physical systems. A good example is classical electromagnetism, which encompasses results derived from gauge symmetry (sometimes called gauge invariance) in a form of a few equations called Maxwell’s equations. The specific mathematical aspects of classical electromagnetic theory are termed “laws of electromagnetism,” reflecting the level of consistent and reproducible evidence that supports them. Within electromagnetic theory generally, there are numerous hypotheses about how electromagnetism applies to specific situations. Many of these hypotheses are already considered to be adequately tested, with new ones always in the making and perhaps untested. An example of the latter might be the radiation reaction force. As of 2009, its effects on the periodic motion of charges are detectable in synchrotrons, but only as averaged effects over time. Some researchers are now considering experiments that could observe these effects at the instantaneous level (i.e. not averaged over time).[54][55]

Reference

  1. National Academy of Sciences (US) (1999). Science and Creationism: A View from the National Academy of Sciences(2nd ed.). National Academies Press. p. 2doi:10.17226/6024ISBN 978-0-309-06406-4PMID 25101403.
  2. The Structure of Scientific Theories. The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University. 2016.
  3. Schafersman, Steven D. “An Introduction to Science”.
  4. “Is Evolution a Theory or a Fact?”National Academy of Sciences. 2008.
  5. Popper, Karl (1963), Conjectures and Refutations, Routledge and Kegan Paul, London, UK. Reprinted in Theodore Schick (ed., 2000), Readings in the Philosophy of Science, Mayfield Publishing Company, Mountain View, Calif.
  6. Andersen, Hanne; Hepburn, Brian (2015). Edward N. Zalta (ed.). Scientific Method. The Stanford Encyclopedia of Philosophy.
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  8. Howard, Don A. (23 June 2018). Zalta, Edward N. (ed.). The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University – via Stanford Encyclopedia of Philosophy.
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  10. Courtney A, Courtney M (2008). “Comments Regarding “On the Nature Of Science””. Physics in Canada. 64 (3): 7–8. arXiv:0812.4932.
  11. Elliott Sober, Let’s Razor Occam’s Razor, pp. 73–93, from Dudley Knowles (ed.) Explanation and Its Limits, Cambridge University Press (1994).
  12. National Academy of Sciences (2008), Science, Evolution, and Creationism.
  13. Hooke, Robert (1635–1703). Micrographia, Observation XVIII.
  14.  Misner, Charles W.; Thorne, Kip S.; Wheeler, John Archibald (1973). Gravitation, p. 1049. New York: W. H.Freeman and Company. ISBN 0-7167-0344-0.
  15. See Acid–base reaction.
  16. Bước lên tới:a b c “Chapter 1: The Nature of Science”. www.project2061.org.
  17. See, for example, Common descent and Evidence for common descent.
  18. For example, see the article on the discovery of Neptune; the discovery was based on an apparent violation of the orbit of Uranus as predicted by Newtonian mechanics. This explanation did not require any modification of the theory, but rather modification of the hypothesis that there were only seven planets in the Solar System.
  19. U. Le Verrier (1859), (in French), “Lettre de M. Le Verrier à M. Faye sur la théorie de Mercure et sur le mouvement du périhélie de cette planète”, Comptes rendus hebdomadaires des séances de l’Académie des sciences (Paris), vol. 49 (1859), pp. 379–83.
  20. For example, the modern theory of evolution (the modern evolutionary synthesis) incorporates significant contributions from R. A. FisherErnst MayrJ. B. S. Haldane, and many others.
  21. Weinberg S (1993). Dreams of a Final Theory: The Scientist’s Search for the Ultimate Laws of Nature.
  22. Maxwell, J. C., & Thompson, J. J. (1892). A treatise on electricity and magnetism. Clarendon Press series. Oxford: Clarendon.
  23. “How the Sun Shines”. www.nobelprize.org.
  24. The strong force, the electroweak force, and gravity. The electroweak force is the unification of electromagnetism and the weak force. All observed causal interactions are understood to take place through one or more of these three mechanisms, although most systems are far too complicated to account for these except through the successive approximations offered by other theories.
  25. Albert Einstein (1905) “Zur Elektrodynamik bewegter Körper Archived 2009-12-29 at the Wayback Machine“, Annalen der Physik 17: 891; English translation On the Electrodynamics of Moving Bodies by George Barker Jefferyand Wilfrid Perrett (1923); Another English translation On the Electrodynamics of Moving Bodies by Megh Nad Saha (1920).
  26. Schwarz, John H (Mar 1998). “Recent developments in superstring theory”. Proceedings of the National Academy of Sciences of the United States of America. 95 (6): 2750–57. Bibcode:1998PNAS…95.2750Sdoi:10.1073/pnas.95.6.2750PMC 19640PMID 9501161.
  27. See Tests of special relativity. Also, for example: Sidney Coleman, Sheldon L. Glashow, Cosmic Ray and Neutrino Tests of Special Relativity, Phys. Lett. B405 (1997) 249–52, found here [1]. An overview can be found here.
  28. Roberto Torretti, The Philosophy of Physics (Cambridge: Cambridge University Press, 1999), pp. 289–90.
  29. “Scientific Laws and Theories”.
  30. See the article on Physical law, for example.
  31. “Definitions of Fact, Theory, and Law in Scientific Work”. 16 March 2016.
  32. “Harding (1999)”.
  33. William F. McComas (30 December 2013). The Language of Science Education: An Expanded Glossary of Key Terms and Concepts in Science Teaching and Learning. Springer Science & Business Media. p. 107. ISBN 978-94-6209-497-0.
  34. “What’s the Difference Between a Scientific Hypothesis, Theory and Law?”.
  35.  Gould, Stephen Jay (1981-05-01). “Evolution as Fact and Theory”. Discover. 2 (5): 34–37.
  36. Further examples are here [2], and in the article on Evolution as fact and theory.
  37. “Essay”. ncse.com. Retrieved 25 March 2015.
  38. Suppe, Frederick (1998). “Understanding Scientific Theories: An Assessment of Developments, 1969–1998” (PDF). Philosophy of Science. 67: S102–S115. doi:10.1086/392812. Retrieved 14 February 2013.
  39. Halvorson, Hans (2012). “What Scientific Theories Could Not Be” (PDF). Philosophy of Science. 79 (2): 183–206. CiteSeerX 10.1.1.692.8455doi:10.1086/664745. Retrieved 14 February 2013.
  40. Frigg, Roman (2006). “Scientific Representation and the Semantic View of Theories” (PDF). Theoria. 55 (2): 183–206. Retrieved 14 February 2013.
  41. Hacking, Ian (1983). Representing and Intervening. Introductory Topics in the Philosophy of Natural Science. Cambridge University Press.
  42. Box, George E.P. & Draper, N.R. (1987). Empirical Model-Building and Response Surfaces. Wiley. p. 424
  43. Lorenzo Iorio (2005). “On the possibility of measuring the solar oblateness and some relativistic effects from planetary ranging”. Astronomy and Astrophysics. 433 (1): 385–93. arXiv:gr-qc/0406041Bibcode:2005A&A…433..385Idoi:10.1051/0004-6361:20047155.
  44. Myles Standish, Jet Propulsion Laboratory (1998)
  45. For example, Reese & Overto (1970); Lerner (1998); also Lerner & Teti (2005), in the context of modeling human behavior.
  46. Isaac Asimov, Understanding Physics (1966) pp. 4–5.
  47. Hawking, Stephen (1988). A Brief History of TimeBantam BooksISBN 978-0-553-38016-3.
  48. Hempel. C.G. 1951 “Problems and Changes in the Empiricist Criterion of Meaning” in Aspects of Scientific Explanation. Glencoe: the Free Press. Quine, W.V.O 1952 “Two Dogmas of Empiricism” reprinted in From a Logical Point of View. Cambridge: Harvard University Press
  49. Philip Kitcher 1982 Abusing Science: The Case Against Creationism, pp. 45–48. Cambridge: The MIT Press
  50. Hempel CG 1952. Fundamentals of Concept Formation in Empirical Science. (Volume 2, #7 of Foundations of the Unity of Science. Toward an International Encyclopedia of Unified Science). University of Chicago Press, p. 36.
  51. Polanyi M. 1958. Personal Knowledge. Towards a Post-Critical Philosophy. London: Routledge & Kegan Paul, p. 4.
  52. Galileo Galilei, The Assayer, as translated by Stillman Drake(1957), Discoveries and Opinions of Galileo pp. 237–38.
  53. Hacking I. 1983. Representing and Intervening. Cambridge University Press, p. 219.
  54. Koga J and Yamagiwa M (2006). Radiation reaction effects in ultrahigh irradiance laser pulse interactions with multiple electrons.
  55. Plass, G.N., 1956, The Carbon Dioxide Theory of Climatic Change, Tellus VIII, 2. (1956), pp. 140–54.

Becoming and evolution of a scientific theory

The process of becoming a scientific theory

The scientific method involves the proposal and testing of hypotheses, by deriving predictions from the hypotheses about the results of future experiments, then performing those experiments to see whether the predictions are valid. This provides evidence either for or against the hypothesis. When enough experimental results have been gathered in a particular area of inquiry, scientists may propose an explanatory framework that accounts for as many of these as possible. This explanation is also tested, and if it fulfills the necessary criteria (see above), then the explanation becomes a theory. This can take many years, as it can be difficult or complicated to gather sufficient evidence.

Once all of the criteria have been met, it will be widely accepted by scientists (see scientific consensus) as the best available explanation of at least some phenomena. It will have made predictions of phenomena that previous theories could not explain or could not predict accurately, and it will have resisted attempts at falsification. The strength of the evidence is evaluated by the scientific community, and the most important experiments will have been replicated by multiple independent groups.

Theories do not have to be perfectly accurate to be scientifically useful. For example, the predictions made by classical mechanics are known to be inaccurate in the relatistivic realm, but they are almost exactly correct at the comparatively low velocities of common human experience.[14] In chemistry, there are many acid-base theories providing highly divergent explanations of the underlying nature of acidic and basic compounds, but they are very useful for predicting their chemical behavior.[15] Like all knowledge in science, no theory can ever be completely certain, since it is possible that future experiments might conflict with the theory’s predictions.[16] However, theories supported by the scientific consensus have the highest level of certainty of any scientific knowledge; for example, that all objects are subject to gravity or that life on Earth evolved from a common ancestor.[17]

Acceptance of a theory does not require that all of its major predictions be tested, if it is already supported by sufficiently strong evidence. For example, certain tests may be unfeasible or technically difficult. As a result, theories may make predictions that have not yet been confirmed or proven incorrect; in this case, the predicted results may be described informally with the term “theoretical”. These predictions can be tested at a later time, and if they are incorrect, this may lead to the revision or rejection of the theory.

Modification and improvement

If experimental results contrary to a theory’s predictions are observed, scientists first evaluate whether the experimental design was sound, and if so they confirm the results by independent replication. A search for potential improvements to the theory then begins. Solutions may require minor or major changes to the theory, or none at all if a satisfactory explanation is found within the theory’s existing framework.[18] Over time, as successive modifications build on top of each other, theories consistently improve and greater predictive accuracy is achieved. Since each new version of a theory (or a completely new theory) must have more predictive and explanatory power than the last, scientific knowledge consistently becomes more accurate over time.

If modifications to the theory or other explanations seem to be insufficient to account for the new results, then a new theory may be required. Since scientific knowledge is usually durable, this occurs much less commonly than modification.[16] Furthermore, until such a theory is proposed and accepted, the previous theory will be retained. This is because it is still the best available explanation for many other phenomena, as verified by its predictive power in other contexts. For example, it has been known since 1859 that the observed perihelion precession of Mercury violates Newtonian mechanics,[19] but the theory remained the best explanation available until relativity was supported by sufficient evidence. Also, while new theories may be proposed by a single person or by many, the cycle of modifications eventually incorporates contributions from many different scientists.[20]

After the changes, the accepted theory will explain more phenomena and have greater predictive power (if it did not, the changes would not be adopted); this new explanation will then be open to further replacement or modification. If a theory does not require modification despite repeated tests, this implies that the theory is very accurate. This also means that accepted theories continue to accumulate evidence over time, and the length of time that a theory (or any of its principles) remains accepted often indicates the strength of its supporting evidence.

Unification

In quantum mechanics, the electrons of an atom occupy orbitals around the nucleus. This image shows the orbitals of a hydrogen atom (spd) at three different energy levels (1, 2, 3). Brighter areas correspond to higher probability density.

In some cases, two or more theories may be replaced by a single theory that explains the previous theories as approximations or special cases, analogous to the way a theory is a unifying explanation for many confirmed hypotheses; this is referred to as unification of theories.[21] For example, electricity and magnetism are now known to be two aspects of the same phenomenon, referred to as electromagnetism.[22]

When the predictions of different theories appear to contradict each other, this is also resolved by either further evidence or unification. For example, physical theories in the 19th century implied that the Sun could not have been burning long enough to allow certain geological changes as well as the evolution of life. This was resolved by the discovery of nuclear fusion, the main energy source of the Sun.[23] Contradictions can also be explained as the result of theories approximating more fundamental (non-contradictory) phenomena. For example, atomic theory is an approximation of quantum mechanics. Current theories describe three separate fundamental phenomena of which all other theories are approximations;[24] the potential unification of these is sometimes called the Theory of Everything.[21]

Example: Relativity

In 1905, Albert Einstein published the principle of special relativity, which soon became a theory.[25] Special relativity predicted the alignment of the Newtonian principle of Galilean invariance, also termed Galilean relativity, with the electromagnetic field.[26] By omitting from special relativity the luminiferous aether, Einstein stated that time dilation and length contraction measured in an object in relative motion is inertial—that is, the object exhibits constant velocity, which is speed with direction, when measured by its observer. He thereby duplicated the Lorentz transformation and the Lorentz contraction that had been hypothesized to resolve experimental riddles and inserted into electrodynamic theory as dynamical consequences of the aether’s properties. An elegant theory, special relativity yielded its own consequences,[27] such as the equivalence of mass and energy transforming into one another and the resolution of the paradox that an excitation of the electromagnetic field could be viewed in one reference frame as electricity, but in another as magnetism.

Einstein sought to generalize the invariance principle to all reference frames, whether inertial or accelerating.[28] Rejecting Newtonian gravitation—a central force acting instantly at a distance—Einstein presumed a gravitational field. In 1907, Einstein’s equivalence principle implied that a free fall within a uniform gravitational field is equivalent to inertial motion.[28] By extending special relativity’s effects into three dimensions, general relativity extended length contraction into space contraction, conceiving of 4D space-time as the gravitational field that alters geometrically and sets all local objects’ pathways. Even massless energy exerts gravitational motion on local objects by “curving” the geometrical “surface” of 4D space-time. Yet unless the energy is vast, its relativistic effects of contracting space and slowing time are negligible when merely predicting motion. Although general relativity is embraced as the more explanatory theory via scientific realism, Newton’s theory remains successful as merely a predictive theory via instrumentalism. To calculate trajectories, engineers and NASA still uses Newton’s equations, which are simpler to operate.[16]

Assumptions in formulating theories

An assumption (or axiom) is a statement that is accepted without evidence. For example, assumptions can be used as premises in a logical argument. Isaac Asimov described assumptions as follows:

…it is incorrect to speak of an assumption as either true or false, since there is no way of proving it to be either (If there were, it would no longer be an assumption). It is better to consider assumptions as either useful or useless, depending on whether deductions made from them corresponded to reality…Since we must start somewhere, we must have assumptions, but at least let us have as few assumptions as possible.[46]

Certain assumptions are necessary for all empirical claims (e.g. the assumption that reality exists). However, theories do not generally make assumptions in the conventional sense (statements accepted without evidence). While assumptions are often incorporated during the formation of new theories, these are either supported by evidence (such as from previously existing theories) or the evidence is produced in the course of validating the theory. This may be as simple as observing that the theory makes accurate predictions, which is evidence that any assumptions made at the outset are correct or approximately correct under the conditions tested.

Conventional assumptions, without evidence, may be used if the theory is only intended to apply when the assumption is valid (or approximately valid). For example, the special theory of relativity assumes an inertial frame of reference. The theory makes accurate predictions when the assumption is valid, and does not make accurate predictions when the assumption is not valid. Such assumptions are often the point with which older theories are succeeded by new ones (the general theory of relativity works in non-inertial reference frames as well).

The term “assumption” is actually broader than its standard use, etymologically speaking. The Oxford English Dictionary (OED) and online Wiktionary indicate its Latin source as assumere (“accept, to take to oneself, adopt, usurp”), which is a conjunction of ad- (“to, towards, at”) and sumere (to take). The root survives, with shifted meanings, in the Italian assumere and Spanish sumir. The first sense of “assume” in the OED is “to take unto (oneself), receive, accept, adopt”. The term was originally employed in religious contexts as in “to receive up into heaven”, especially “the reception of the Virgin Mary into heaven, with body preserved from corruption”, (1297 CE) but it was also simply used to refer to “receive into association” or “adopt into partnership”. Moreover, other senses of assumere included (i) “investing oneself with (an attribute)”, (ii) “to undertake” (especially in Law), (iii) “to take to oneself in appearance only, to pretend to possess”, and (iv) “to suppose a thing to be” (all senses from OED entry on “assume”; the OED entry for “assumption” is almost perfectly symmetrical in senses). Thus, “assumption” connotes other associations than the contemporary standard sense of “that which is assumed or taken for granted; a supposition, postulate” (only the 11th of 12 senses of “assumption”, and the 10th of 11 senses of “assume”).

Reference

  1. National Academy of Sciences (US) (1999). Science and Creationism: A View from the National Academy of Sciences(2nd ed.). National Academies Press. p. 2. doi:10.17226/6024. ISBN 978-0-309-06406-4. PMID 25101403.
  2. The Structure of Scientific Theories. The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University. 2016.
  3. Schafersman, Steven D. “An Introduction to Science”.
  4. “Is Evolution a Theory or a Fact?”. National Academy of Sciences. 2008.
  5. Popper, Karl (1963), Conjectures and Refutations, Routledge and Kegan Paul, London, UK. Reprinted in Theodore Schick (ed., 2000), Readings in the Philosophy of Science, Mayfield Publishing Company, Mountain View, Calif.
  6. Andersen, Hanne; Hepburn, Brian (2015). Edward N. Zalta (ed.). Scientific Method. The Stanford Encyclopedia of Philosophy.
  7. The Devil in Dover,
  8. Howard, Don A. (23 June 2018). Zalta, Edward N. (ed.). The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University – via Stanford Encyclopedia of Philosophy.
  9. Alan Baker (2010) [2004]. “Simplicity”. Stanford Encyclopedia of Philosophy. California: Stanford University. ISSN 1095-5054.
  10. Courtney A, Courtney M (2008). “Comments Regarding “On the Nature Of Science””. Physics in Canada. 64 (3): 7–8. arXiv:0812.4932.
  11. Elliott Sober, Let’s Razor Occam’s Razor, pp. 73–93, from Dudley Knowles (ed.) Explanation and Its Limits, Cambridge University Press (1994).
  12. National Academy of Sciences (2008), Science, Evolution, and Creationism.
  13. Hooke, Robert (1635–1703). Micrographia, Observation XVIII.
  14.  Misner, Charles W.; Thorne, Kip S.; Wheeler, John Archibald (1973). Gravitation, p. 1049. New York: W. H.Freeman and Company. ISBN 0-7167-0344-0.
  15. See Acid–base reaction.
  16. Bước lên tới:a b c “Chapter 1: The Nature of Science”. www.project2061.org.
  17. See, for example, Common descent and Evidence for common descent.
  18. For example, see the article on the discovery of Neptune; the discovery was based on an apparent violation of the orbit of Uranus as predicted by Newtonian mechanics. This explanation did not require any modification of the theory, but rather modification of the hypothesis that there were only seven planets in the Solar System.
  19. U. Le Verrier (1859), (in French), “Lettre de M. Le Verrier à M. Faye sur la théorie de Mercure et sur le mouvement du périhélie de cette planète”, Comptes rendus hebdomadaires des séances de l’Académie des sciences (Paris), vol. 49 (1859), pp. 379–83.
  20. For example, the modern theory of evolution (the modern evolutionary synthesis) incorporates significant contributions from R. A. Fisher, Ernst Mayr, J. B. S. Haldane, and many others.
  21. Weinberg S (1993). Dreams of a Final Theory: The Scientist’s Search for the Ultimate Laws of Nature.
  22. Maxwell, J. C., & Thompson, J. J. (1892). A treatise on electricity and magnetism. Clarendon Press series. Oxford: Clarendon.
  23. “How the Sun Shines”. www.nobelprize.org.
  24. The strong force, the electroweak force, and gravity. The electroweak force is the unification of electromagnetism and the weak force. All observed causal interactions are understood to take place through one or more of these three mechanisms, although most systems are far too complicated to account for these except through the successive approximations offered by other theories.
  25. Albert Einstein (1905) “Zur Elektrodynamik bewegter Körper Archived 2009-12-29 at the Wayback Machine”, Annalen der Physik 17: 891; English translation On the Electrodynamics of Moving Bodies by George Barker Jefferyand Wilfrid Perrett (1923); Another English translation On the Electrodynamics of Moving Bodies by Megh Nad Saha (1920).
  26. Schwarz, John H (Mar 1998). “Recent developments in superstring theory”. Proceedings of the National Academy of Sciences of the United States of America. 95 (6): 2750–57. Bibcode:1998PNAS…95.2750S. doi:10.1073/pnas.95.6.2750. PMC 19640. PMID 9501161.
  27. See Tests of special relativity. Also, for example: Sidney Coleman, Sheldon L. Glashow, Cosmic Ray and Neutrino Tests of Special Relativity, Phys. Lett. B405 (1997) 249–52, found here [1]. An overview can be found here.
  28. Roberto Torretti, The Philosophy of Physics (Cambridge: Cambridge University Press, 1999), pp. 289–90.
  29. “Scientific Laws and Theories”.
  30. See the article on Physical law, for example.
  31. “Definitions of Fact, Theory, and Law in Scientific Work”. 16 March 2016.
  32. “Harding (1999)”.
  33. William F. McComas (30 December 2013). The Language of Science Education: An Expanded Glossary of Key Terms and Concepts in Science Teaching and Learning. Springer Science & Business Media. p. 107. ISBN 978-94-6209-497-0.
  34. “What’s the Difference Between a Scientific Hypothesis, Theory and Law?”.
  35.  Gould, Stephen Jay (1981-05-01). “Evolution as Fact and Theory”. Discover. 2 (5): 34–37.
  36. Further examples are here [2], and in the article on Evolution as fact and theory.
  37. “Essay”. ncse.com. Retrieved 25 March 2015.
  38. Suppe, Frederick (1998). “Understanding Scientific Theories: An Assessment of Developments, 1969–1998” (PDF). Philosophy of Science. 67: S102–S115. doi:10.1086/392812. Retrieved 14 February 2013.
  39. Halvorson, Hans (2012). “What Scientific Theories Could Not Be” (PDF). Philosophy of Science. 79 (2): 183–206. CiteSeerX 10.1.1.692.8455. doi:10.1086/664745. Retrieved 14 February 2013.
  40. Frigg, Roman (2006). “Scientific Representation and the Semantic View of Theories” (PDF). Theoria. 55 (2): 183–206. Retrieved 14 February 2013.
  41. Hacking, Ian (1983). Representing and Intervening. Introductory Topics in the Philosophy of Natural Science. Cambridge University Press.
  42. Box, George E.P. & Draper, N.R. (1987). Empirical Model-Building and Response Surfaces. Wiley. p. 424
  43. Lorenzo Iorio (2005). “On the possibility of measuring the solar oblateness and some relativistic effects from planetary ranging”. Astronomy and Astrophysics. 433 (1): 385–93. arXiv:gr-qc/0406041. Bibcode:2005A&A…433..385I. doi:10.1051/0004-6361:20047155.
  44. Myles Standish, Jet Propulsion Laboratory (1998)
  45. For example, Reese & Overto (1970); Lerner (1998); also Lerner & Teti (2005), in the context of modeling human behavior.
  46. Isaac Asimov, Understanding Physics (1966) pp. 4–5.
  47. Hawking, Stephen (1988). A Brief History of Time. Bantam Books. ISBN 978-0-553-38016-3.
  48. Hempel. C.G. 1951 “Problems and Changes in the Empiricist Criterion of Meaning” in Aspects of Scientific Explanation. Glencoe: the Free Press. Quine, W.V.O 1952 “Two Dogmas of Empiricism” reprinted in From a Logical Point of View. Cambridge: Harvard University Press
  49. Philip Kitcher 1982 Abusing Science: The Case Against Creationism, pp. 45–48. Cambridge: The MIT Press
  50. Hempel CG 1952. Fundamentals of Concept Formation in Empirical Science. (Volume 2, #7 of Foundations of the Unity of Science. Toward an International Encyclopedia of Unified Science). University of Chicago Press, p. 36.
  51. Polanyi M. 1958. Personal Knowledge. Towards a Post-Critical Philosophy. London: Routledge & Kegan Paul, p. 4.
  52. Galileo Galilei, The Assayer, as translated by Stillman Drake(1957), Discoveries and Opinions of Galileo pp. 237–38.
  53. Hacking I. 1983. Representing and Intervening. Cambridge University Press, p. 219.
  54. Koga J and Yamagiwa M (2006). Radiation reaction effects in ultrahigh irradiance laser pulse interactions with multiple electrons.
  55. Plass, G.N., 1956, The Carbon Dioxide Theory of Climatic Change, Tellus VIII, 2. (1956), pp. 140–54.

List of Art movements

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 0-9 & other

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A

abstract art

abstract expressionism

action painting

actualism

aerial perspective

aestheticism

all-over painting

art informel

art of the Third Reich

arte mat

arte povera

arts and crafts movement

asymmetry

automatism

B

bauhaus

blaue reiter

body art

C

camera lucida

camera obscura

Caravaggism

chiaroscuro

classicism

COBRA

cold art

color field painting

conceptual art

concrete art

constructivism

costruzione leggitima

cubism

D

dada

de stijl

decorum

die brucke

divisionism

E

earth works

ecological art

electronic art

environment art

equilibrium

event-structure

expressionism

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F

Fauvism

feminist aesthetics

formalism

Freudian aesthetics

fundamental art

futurism

G

H

happening

Hogarth’s line

humanism

I

idealization

ideoplastic

illusionism

imagism

impressionism

J

Jungian aesthetics

K

kalte kunst

kinetic art

L

land art

lettrism

Lysippan proportions

M

magic realism

mannerism

Marxist criticism

minimalism

modernism

movimento spaziale

Munsell’s theory

N

naturalism

Nazarene brotherhood

Nazi art

neo-classicism

neo-impressionism

Neue Sachlichkeit

nouveau rialisme

nouvelle tendance

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O

op art

orphism

P

perspective

photo-realism

picture plane

picturesque

pointillism

Polyclitan school

pop art

post-Impressionism

post-modernism

post-painterly abstraction

Poussinism

pre-Raphaelite

primitivism

process art

proportion

purism

purism (of ‘machine art’)

Q

R

rayonism

realism

regionalism

romanticism

Rubenism

S

scapigliatura

section d’or

simultaneisme

situationism

socialist realism

sotto in su

spatialism

structurism

sublimity

suprematism

surrealism

symbolism

synchromism

synthetism

T

tachism

trompe I’oeil

U

ut pictura poesis

V

verismo

virtual reality

vorticism

W

 

X

 

Y

Z

0-9 & other

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Political Theories and Concepts

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 0-9 & other

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A

absolutism

action theory

activism

administrative theory

alienation

anarchism

anarcho-capitalism

anarcho-feminism

anarcho-syndicalism

androcentrism

anomie

apartheid

aristocracy

Aristotelianism

Austinianism

authoritarianism

authority

autocracy

B

backlash theory

Bakuninism

balance of power

balance of terror

Balkanization

bargaining theory

behavioralism

Bentham’s theory of utilitarianism

billiard ball model

biological determinism

black box model

Blanquism

bolshevism

budget-maximization theory

bureaucracy

C

capital logic

catallaxy

catastrophe theory

centralization

chicken

Christian socialism

circulation of elites

citizenship

civil disobedience

civil society

class dealignment

class struggle

class voting

clerisy

cock-up theory

collective security

collectivism

collegialism

colonialism

common good

communalism

communications theory

communism

communitarianism

complex interdependence

conflict theory

consciousness raising

consent

conservatism

conservative paradox

conspiracy

constitutionalism

constructive apathy

contingency theory

convergence theory

corporatism

countervailing power

crisis management

crisis of capitalism

crisis theory

critical theory

cybernetics

cyclical theory

D

decision making theory

decline of the West

deference

democracy

democratic centralism

democratic elitism

dependency theory

deterrence

detonator theory

development theory

dialectical materialism

dictatorship of the proletariat

difference principle

direct action

direct democracy

directed democracy

distributism

divine right

dominant ideology

domino theory

doomsday theory

double consciousness

dual state theory

E

economic determinism

egalitarianism

electoral competition

elitism

embourgeoisement

encroaching control

end of ideology

equal freedom

equality

equality of states doctrine

equilibrium theory

Erastianism

escalation

essential contestability

essentialism

evolutionism

exclusion theory

exit, voice, and loyalty

exploitation

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F

Fabianism

false consciousness

fascism

federalism

feminism

feminist linguistics

feminist methodology

fetishism

feudalism

foco theory

functionalism

G

game theory

gatekeeping theory

gaze

gender theory

general strike

general will

geopolitics

grand theory

great man theory

greatest happiness principle

Grotian theory

grounded theory

group theory

guild socialism

H

heartland theory

hegemonic stability theory

hegemony

high politics

historical materialism

human imperfection

human nature

hype

I

ideology

immiseration

impacted pluralism

imperialism

incrementalism

individualism

industrial democracy

inevitability of gradualness

interests

internal colonialism

international morality

international system

internationalism

iron law of oligarchy

isolationism

J

just war

justice

K

king’s two bodies

L

law of the small number

legal positivism

legitimacy

legitimacy crisis

Leninism

liberal democracy

liberal feminism

liberalism

libertarianism

logic of collective action

M

Machiavellianism

managerial revolution

managerialism

Maoism

market socialism

Marxism

Marxist feminism

mass society

master race

materialist theory of history

mercantilism

meritocracy

millenarianism

modernization

mood theory

multilateralism

mutual aid

mutually assured destruction

myth

N

nationalism

natural justice

natural law

natural rights

neo-conservatism

neo-corporatism

neo-functionalism

neo-liberalism

neo-Marxism

new age

new class

new left

new liberalism

new right

NIMBY

noblesse oblige

O

oligarchy

open society

organic theory of the state

overkill

overload theory

Owenism

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P

pacifism

para bellum

paternalism

patriarchy

PCism

peaceful co-existence

permanent revolution

personal is political

piecemeal social engineering

pluralism

plutocracy

police state

polis

political correctness

political culture

political obligation

polyarchy

populism

positive law

possibilism

post-materialism

post-modernism

power

power corrupts

prisoner’s dilemma

privatization

progress

proletarianism

propaganda by the deed

property

property is theft

public choice

public interest

public private divide

Q

R

racism

radical feminism

radicalism

raison d’etat

rational choice

real self

realism

relative autonomy

relative deprivation

representation

republicanism

revisionism

revolution

rights

rule of law

S

satyagraha

separation of powers

separatism

sexism

situationism

social choice

social contract

social credit

social Darwinism

social democracy

socialism

socialism in one country

sovereignty

spontaneous order

Stalinism

state

state capitalism

state of nature

structural functionalism

subsidiarity

survival of the fittest

syndicalism

systems theory

T

Thatcherism

three worlds theory

toryism

total war

totalitarianism

tradition

tragedy of the commons

trahison des clercs

Trotskyism

tyranny of the majority

U

unilateralism

utopianism

V

vanguard party

veil of ignorance

virtual representation

volonte generale

W

welfarism

white man’s burden

withering away of the state

workers’ control

world society

X

Y

Z

zero-sum

0-9 & other

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Philosophical Theories and Concept

A philosophical theory or philosophical position is a view that attempts to explain or account for a particular problem in philosophy. The use of the term “theory” is a statement of colloquial English and not reflective of the term theory. While any sort of thesis or opinion may be termed a position, in analytic philosophy it is thought best to reserve the word “theory” for systematic, comprehensive attempts to solve problems.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 0-9 & other

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A

abandonment

absence paradox

absolute

absolutism

abstractionism

act utilitarianism

activism

agnosticism

altruism

analytic/synthetic

animism

anomalous monism

anthropomorphism

anthroposophy

anti-nomianism

anti-realism

apriorism

Aristotelianism

Aristotle’s four causes

associationism

atheism

atomic uniformity, principle of

atomism

attitude theories

B

Bayesianism

behaviorism

bivalence, law or principle of

Boo Hurrah theory

British empiricists

bundle theories

Buridan’s ass

C

categorical imperative

category mistake

causal principle

causal realism

causal theories

causal theories of meaning

causal theories of perception

causal theories of reference

causal theory of knowledge

causal theory of memory

causal theory of names

chain of being

charity, principle of

classical theory of probability

coherence theory of truth

compatibilism

computational psychology

conceptualism

confirmation principle

Confucianism

connectionism

connexive implication

consequentialism

consistent empiricism

constructivism

contextualism

continental rationalists

continuity, law or principle of

contractualism

contradiction, law of

convention t

conventionalism

correspondence or relational theories of meaning

correspondence theory of truth

counterpart theory

covering law model

Craig’s theorem

creative evolution

critical realism

cynicism

D

de facto and de jure theories of meaning

deduction theorem

deductivism

degrees of truth

deism

denotation and connotation

deontology

descriptions, theory of

descriptive theory of names

descriptivism

determinism

dialectic

dialetheism

double aspect theory of mind

double effect doctrine

double negation principle

dualism

E

eclecticism and syncretism

effluxes, theory of

egocentric predicament

egoism

Eleaticism

emergence theories

emotive theory of truth

emotivism

empiricism

empiriocriticism

Epicureanism

epiphenomenalism

epistemic closure, principle of

essentialism

excluded middle, law of

existentialism

extensionality thesis

externalism

F

fact/value distinction

fallibilism

falsificationism

fatalism

fideism

‘Fido’-Fido theories

finalism

finitism

five ways

folk psychology

formalism

foundationalism

four humors

frequency theory of probability

functionalism

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G

golden rule

Goodman’s paradox

greatest happiness principle

H

haecceitism

hedonism

hedonistic utilitarianism

Hempel’s paradox

hermeneutics

historicism

holism

holistic explanation

human nature

humanity, principle of

Hume’s law

hylomorphism

hylozoism

hypothetico-deductive method

I

ideal utilitarianism

idealism

ideational theories of meaning

identity, law of

identity of indiscernibles

identity theory of mind

identity theory of predication

identity theory of truth

ideology

immaterialism

impossibility of a gambling system, principle of the

improbabilism

indeterminacy of reference and translation

indeterminism

indifference, principle of

indiscernibility of identicals

individuation principle

induction

inductivism

infinite divisibility

innate ideas

inscriptionism

instrumentalism

interactionism

internal relations, doctrine of

internalism

intuitionism

isolationism

J

Jourdain’s paradox

justice

K

L

language of thought

lawyer paradox

legal positivism

legitimacy

Leibniz’s law

libertarianism

limited independent variety, principle of

linguistic phenomenology

linguistic philosophy

local sign theory

logical atomism

logical empiricism

logical positivism

logical relation theory of probability

logicism

M

Manicheism

materialism

mean, doctrine of the

meaning, theories of

mechanism

Meinong’s jungle

meliorism

mereology

metalanguage

methodological theories

modal realism

monism

moral sense theories

mysticism

N

naive realism

naming theories of meaning

nativism

naturalism

naturalized epistemology

necessitarianism

negation, performative theory of

negative utilitarianism

neo-Platonism

neo-Pythagoreanism

neutral monism

new riddle of induction

Nicod’s criterion

nihilism

no-ownership theory of the mind

nominalism

non-cognitivism

O

objective idealism

objectivism

objectivism (2)

occasionalism

Ockham’s Razor

one over many principle

ontology

operationalism

organic unities, principle of

organicism

origins of life

Orphism

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P

panpsychism

pantheism

paraconsistency

paradigmatism

parsimony, principle of

particularism

Pascal’s wager

perfection, principle of

performative, theory of truth

personalism

perspective realism

perspectivism

phenomenalism

phenomenology

physicalism

picture theory of meaning

Plato’s theory of forms

Platonism

plenitude, principle of

plurality of causes

positivism

pragmatic theory of truth

pragmatism

pre-established harmony, doctrine of

preference utilitarianism

prescriptivism

private language argument

probabilism

process philosophy

propensity theory of probability

psychologism

psychophysical parallelism

Pyrrhonism

Pythagoreanism

Q

R

radical empiricism

radical interpretation

range theories of probability

rationalism

real self

realism

reducibility, axiom of

reductionism (1)

reductionism (2)

redundancy theory of truth

regularity theory of causation

relativism

relevance logics

relevant alternatives, theory of

reliabilism

representationalism

resemblance theories of universals

retributivism

rule utilitarianism

S

semantic atomism

semantics

semantics, truth-conditional

sensationalism

sense and reference

situationism

skepticism

solipsism

speciation, theory of

species essentialism

species, theory of

speciesism

specious present

speech act theory

stimulus-response model

Stoicism

subjective idealism

subjectivism

subjectivist theories of probability

sufficient reason, principle of

T

tacit knowledge

teleology

theism

third man argument

three laws of thought

trace theory of memory

transcendental idealism

trialism

Tristram Shandy paradox

tropisms, theory of

truth theory

truth-conditional semantics

types, ramified theory of

types, simple theory of

U

uniformity of nature, principle of the

universalism

universalizability

use theories of meaning

utilitarianism

utilitarianism, Bentham’s theory of

utopianism

V

verifiability principle

vicious circle principle

Vienna Circle

vitalism

voluntarism

W

X

Y

Z

0-9 & other

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Social Theories and Concepts

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 0-9 & other

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A

action theory

altruism

anarcho-syndicalism

androcentrism

anomie

apartheid

aristocracy

atavism

B

biological determinism

bureaucracy

C

collectivism

communications theory

conflict theory

corporatism

D

E

eugenics

exclusion theory

F

feminist linguistics

feminist methodology

functionalism

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G

grand theory

grounded theory

H

historical materialism

human nature

I

internal colonialism

J

K

L

law of the small number

M

Marxism

mass society

N

new age

O

P

piecemeal social engineering

power

public interest

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Q

R

racism

relative deprivation

S

social Darwinism

sociobiology

spontaneous order

structural functionalism

survival of the fittest

systems theory

T

Terms of Use

U

V

W

X

Y

Z

0-9 & other

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Economic Theories and Concepts

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 0-9 & other

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A

ability-to-pay principle

absolute advantage theory

absolute income hypothesis

acceleration principle

adaptive expectations

adding-up problem

administered pricing

adverse selection

Agency theory

aggregate demand theory

Allais paradox

anarcho-syndicalism

Ansoff Matrix

arbitrage pricing policy

Arrow-Debreu model

asymmetrical information

average cost pricing

axiomatic theories

B

balanced budget multiplier

Behavioral theory of the firm

benefit approach principle

Bernoulli’s hypothesis

Bertrand duopoly model

bilateral monopoly

bimetallism

bionomics

Blue Ocean (Strategy)

bounded rationality

bureaucracy

business cycle

C

Cambridge capital controversies

capital asset pricing model

capital logic

capital theory

catallaxy

catastrophe theory

central place theory

CES production function

class struggle

classical macroeconomic model

classical theory of money

clubs, theory of

co-operative games theory

Coase theorem

Cobb-Douglas production function

cobweb theory

collective bargaining theory

collusion theory

colonialism

commodity theory of money

comparative costs

compensation principle

Competitive Advantage

Competitive Advantage (Theory)

composite commodity

Condorcet’s principle

consumer demand, theory of

consumer surplus

contestable markets theory

Contingency Theory

continuity thesis

contract theory

convergence theory

core, theory of the

corporatism

cost-benefit analysis

cost-push inflation

countervailing power

Cournot duopoly model

Cramer’s rule

crisis of capitalism

crowding hypothesis

crowding-out

currency principle

customs union theory

cyclical theory

D

decision theory

DeLorean theory

demand for money theory

demand theory

demand-pull inflation

demographic transition

dependency theory

differential rent theory

diminishing returns, law of

disequilibrium theory

distribution theory

distributism

Diversification strategy

dual decision hypothesis

dual economy theory

dual labor market theory

duopoly theory

E

economic liberalism

economic methodology

economic theory of politics

economic theory of the state

efficient market hypothesis

Engel’s law

entitlement theorem

envelope theorem

equal sacrifice theory

equilibrium theory

Euler’s theory

Evolutionary Theory of the Firm

exploitation

externalities

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F

factor-price equalization theorem

falling rate of profit

fine tuning

firm, theory of the

fixed point theorems

forced saving

free banking theory

free rider problem

fundamental disquilibrium

G

game theory

general equilibrium theory

general strike

general theory of employment, interest and money

Gibrat’s rule of proportionate growth

Giffen paradox

golden rule of capital accumulation

gravity model

Gresham’s law

group theory

growth of the firm, theory of the

growth-pole theory

Ansoff Matrix

H

Harrod-Domar growth model

Heckscher-Ohlin trade theory

Hicks-Hansen model

historical materialism

Hotelling’s law

human capital theory

Hypercompetition theory

I

imperfect competition

imperialism

impossibility theorem

income determination, theory of

income distribution, theory of

information theory

input-output analysis

insider-outsider wage determination

Institutional Theory

internal and external balance

invisible hand (theory)

iron law of wages

IS-LM model

J

just price

K

Keynesian economics

Kondratieff cycles

L

labor force participation

labor market discrimination

labor theory of value

Laffer curve

laissez-faire

Law of diminishing returns

large numbers, law of

Le Chatelier principle

learning-by-doing

least cost location theory

Leontief paradox

life-cycle hypothesis

Lindahl equilibrium

linear programming

List of Economic theories and concepts

loanable funds theory of the rate of interest

long wages

lump-of-labor theory of wages

Lyapunov’s theorem

M

machinery question

Malthusian population theory

managerial theories of the firm

marginal cost pricing

marginal efficiency of capital

marginal productivity theory of distribution

marginal utility theory

mark-up pricing

Market penetration strategy

Market development strategy

market socialism

markets, law of

Marshall-Lerner principle

Marxism

material balances principle

measure theory

mercantilism

Modigliani-Miller theory of the cost of capital

monetarism

monopolistic competition

monopoly

monopoly capitalism

moral hazard

multiplier

multiplier-accelerator

N

NAIRU

Nash equilibrium

national income

nationalization

natural and warranted rates of growth

natural monopoly of economics

natural rate of unemployment

negative income tax

neo-classical growth theory

neo-classical theory

neo-Ricardian theory

new class

new classical macroeconomics

non-accelerating inflation rate of unemployment

non-competing groups

non-nested hypothesis

non-profit organization

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O

occupation segregation

Okun’s law

oligopoly theory

opportunity cost

optimal tariff theory

option pricing theory

Organizational Ecology (Theory)

Organizational learning theory

Organizational Power (Theory)

Organizational structure (Theory)

organization theory

own rate of interest

P

paradox of thrift

paradox of value

paradox of voting

Pareto efficiency

Pareto optimality

partial equilibrium theory

peak-load pricing

perfect competition

permanent income hypothesis

Phillips curve

Physiocracy

Pigou effect

political business cycle

portfolio selection theory

Prebisch-Singer thesis

price discrimination

Privacy Policy

privatization

Product development strategy

product life-cycle theory

Product market development matrix / Product market matrix / Product-market strategy

production, theory of

profits, theories of

property

Property Rights (Theory)

public choice

public utility pricing

purchasing power parity

Q

quantity theory of money

queuing theory

R

Ramsey pricing

random walk hypothesis

rational expectations theory

rationing

Rawls theory of justice

Reaganomics

real bills doctrine

regulation

regulatory capture

relative income hypothesis

rent seeking

Resource dependence (theory)

Resource-based theory

returns to scale

revealed preference theory

Ricardian equivalence theorem

roundabout method of production

Rybczynski theorem

S

satisficing

Say’s law

Scitovsky paradox

screening hypothesis

search theory

second best, theory of

secular stagnation theory

segmented labor market theory

shadow pricing

signalling

Slutsky’s theorem

small is beautiful principle

social welfare function

Solow economic growth

specie-flow mechanism

St Petersburg paradox

stationary state

stock-flow analysis

structure-conduct-performance theory

substitution theory

sunspot theory

supply-side economics

surplus value

syndicalism

Systems Theory

T

tax incidence

technological gap theory

term structure of interest rates

Thatcherism

Tiebout hypothesis

time preference theory of interest

trade cycle

Transaction Cost Economics

trickle-down theory

turnpike theory

U

uncertainty

underconsumption theory

unemployment

V

variable proportions, law of

vent for surplus

Verdoorn’s law

Visible Hand (Theory)

VRIN model or VRIO framework

W

wages fund doctrine

Wagner’s law

Walras’s stability

Weber’s theory of the location of the firm

Wicksell’s theory of capital

X

x-efficiency

Y

Z

0-9 & other

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Entrepreneurship and Startup

Running any business is a matter of much dedication, strategy planning as well as having an eye for detail. With proper coordination of your ideas, you can ensure that the company thrives. There are different kinds of business. While some are termed as start-ups, and the others are called entrepreneurship. It is a notable fact that all entrepreneurship are not startup as well as there are certain fundamental differences between the two. This difference has to be understood thoroughly to run a successful business. The major differences lie in the concept of entrepreneurship and startup as well as when you have a clear understanding of the terms as well as the characteristics of the types of companies you can ensure that you can master the business on your own.

Entrepreneurship refers to all business ventures, new or old. It includes sole-proprietorship, small businesses, partnerships, firms, and corporations. It can be based on an existing idea or on a new idea.

Startup: In the most basic sense, a startup is a newly emerged business venture. It is started by individual founders to meet a market gap. Founders are new or serial entrepreneurs. Nowadays, startups mostly mean new businesses that are solving market’s problems with unique ideas. A startup seeks to create a viable and scalable business model.

Startups do differ from entrepreneurships. Startups intend to solve problems uniquely and to grow large. Start-ups face high uncertainty and have high rates of failure. A minority go on to be highly successful and influential.

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Economics of the Firm

Economics of the Firm focuses on the economic issues and problems related to business organization, management, and strategy. Issues and problems include: an explanation of why corporate firms emerge and exist; why they expand: horizontally, vertically and spacially; the role of entrepreneurs and entrepreneurship; the significance of organizational structure; the relationship of firms with employees, providers of capital, customers, and government; and interactions between firms and the business environment.

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Firm Strategy and Strategic Management

In the field of management, a firm strategy is a comprehensive plan to achieve its goals in the face of these conditions. Strategy defines how a firm will achieve long-term success. Strategy is defined as “the determination of the basic long-term goals of an enterprise, and the adoption of courses of action and the allocation of resources necessary for carrying out these goals” (Chandler, 1962) Strategies are established to set direction, focus effort, define or clarify the organization, and provide consistency or guidance in response to the environment (Mintzberg, 1987). Determining the strategy is a critical decision for management because it involves a significant commitment of resources and, once initiated, it is very difficult and costly to change.

Firm strategy involves the formulation and implementation of the major goals and initiatives taken by an organization’s managers on behalf of stakeholders, based on consideration of resources and an assessment of the internal and external environments in which the organization operates. Firm strategy provides overall direction to an enterprise and involves specifying the organization’s objectives, developing policies and plans to achieve those objectives, and then allocating resources to implement the plans. Academics and practicing managers have developed numerous models and frameworks to assist in strategic decision-making in the context of complex environments and competitive dynamics. Firm strategy is not static in nature; the models often include a feedback loop to monitor execution and to inform the next round of planning.

Michael Porter identifies three principles underlying strategy:

  • creating a “unique and valuable [market] position”
  • making trade-offs by choosing “what not to do”
  • creating “fit” by aligning company activities with one another to support the chosen strategy

Management theory and practice often make a distinction between strategic management and operational management, with operational management concerned primarily with improving efficiency and controlling costs within the boundaries set by the organization’s strategy.

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Human Resource Management and Organizational Culture

Human resource management (HRM or HR) is the strategic approach to the effective management of people in a company or organization such that they help their business gain a competitive advantage. It is designed to maximize employee performance in service of an employer’s strategic objectives. Human resource management is primarily concerned with the management of people within organizations, focusing on policies and systems. HR departments are responsible for overseeing employee-benefits design, employee recruitment, training and development, performance appraisal, and reward management, such as managing pay and Employee benefits benefit systems. HR also concerns itself with organizational change and industrial relations, or the balancing of organizational practices with requirements arising from collective bargaining and governmental laws.

The overall purpose of human resources (HR) is to ensure that the organization is able to achieve success through people. HR professionals manage the human capital of an organization and focus on implementing policies and processes. They can specialize in finding, recruiting, training, and developing employees, as well as maintaining employee relations or benefits. Training and development professionals ensure that employees are trained and have continuous development. This is done through training programs, performance evaluations, and reward programs. Employee relations deals with the concerns of employees when policies are broken, such as cases involving harassment or discrimination. Managing employee benefits includes developing compensation structures, parental leave programs, discounts, and other benefits for employees. On the other side of the field are HR generalists or business partners. These HR professionals could work in all areas or be labour relations representatives working with unionized employees.

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Organizational Culture: Definition, Importance, and Development

What is organizational culture?

Organizational culture is the collection of values, expectations, and practices that guide and inform the actions of all team members. Think of it as the collection of traits that make your company what it is. A great culture exemplifies positive traits that lead to improved performance, while a dysfunctional company culture brings out qualities that can hinder even the most successful organizations.

Don’t confuse culture with organizational goals or a mission statement, although both can help define it. Culture is created through consistent and authentic behaviors, not press releases or policy documents. You can watch company culture in action when you see how a CEO responds to a crisis, how a team adapts to new customer demands, or how a manager corrects an employee who makes a mistake.

The importance of culture to your company

Organizational culture affects all aspects of your business, from punctuality and tone to contract terms and employee benefits. When workplace culture aligns with your employees, they’re more likely to feel more comfortable, supported, and valued. Companies that prioritize culture can also weather difficult times and changes in the business environment and come out stronger.

Culture is a key advantage when it comes to attracting talent and outperforming the competition. 77 percent of workers consider a company’s culture before applying, and almost half of employees would leave their current job for a lower-paying opportunity at an organization with a better culture. The culture of an organization is also one of the top indicators of employee satisfaction and one of the main reasons that almost two-thirds (65%) of employees stay in their job.

Consider Microsoft and Salesforce. Both technology-based companies are world-class performers and admired brands, and both owe this in part to prioritizing culture. Microsoft, known for its cut-throat competitiveness under Steve Balmer, has been positively transformed by Satya Nadella, who took over as CEO of the company in 2014. He embarked on a program to refine the company culture, a process that upended competitiveness in favor of continuous learning. Instead of proving themselves, employees were encouraged to improve themselves. Today Microsoft’s market cap flirts with $1 trillion and it is again competing with Apple and Amazon as one of the most valuable companies in the world.

Salesforce puts corporate culture front and center and has experienced incredible growth throughout its history. Marc Benioff, Salesforce’s founder and CEO, established philanthropic cultural norms that have guided the company over the past two decades. All new Salesforce employees spend part of their first day volunteering and receive 56 hours of paid time to volunteer a year. This focus on meaning and mission has made Salesforce one of the best places to work in America according to Fortune, and it hasn’t compromised profits either: Salesforce’s stock price has surged year after year at an average of over 26% annually to date.

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