From theory to data - Historique des versions

Arthur : /* Criteria for the Scientificity of Assumptions */

2021-02-05T07:31:56Z

Criteria for the Scientificity of Assumptions

← Version précédente		Version du 5 février 2021 à 09:31
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	*a hypothesis must be formulated in such a way that it is falsifiable.		*a hypothesis must be formulated in such a way that it is falsifiable.

	The controllability of a hypothesis is fundamental~~, we~~ must be able to compare it with field data. The hypothesis must be controllable.		The controllability of a hypothesis is fundamental. We must be able to compare it with field data. The hypothesis must be controllable.

	According to Popper and Kuhn, a hypothesis must be falsifiable. This gives the hypothesis a scientific character, because a good hypothesis must be refutable. For example, according to Popper, the proposition "~~god~~ exists" is not a hypothesis because it is not refutable; however, the hypothesis "all swans are white" is falsifiable because they may be of a different ~~color~~. Thus the main characteristic that gives the relevance of a hypothesis is the fact that it is falsifiable.		According to Popper and Kuhn, a hypothesis must be falsifiable. This gives the hypothesis a scientific character because a good hypothesis must be refutable. For example, according to Popper, the proposition "God exists" is not a hypothesis because it is not refutable; however, the hypothesis "all swans are white" is falsifiable because they may be of a different colour. Thus the main characteristic that gives the relevance of a hypothesis is the fact that it is falsifiable.
	*'''falsifiable hypotheses''': heavy objects tend down if nothing holds them back; it rains every Thursday.		*'''falsifiable hypotheses''': heavy objects tend down if nothing holds them back; it rains every Thursday.
	*'''non-falsifiable hypotheses''': either it rains or it does not rain; all the points of the circle are equidistant from the centre.		*'''non-falsifiable hypotheses''': either it rains, or it does not rain; all the points of the circle are equidistant from the centre.

	To sum up, the hypothesis to meet the criterion of scientificity must be falsifiable.		To sum up, the hypothesis to meet the criterion of scientificity must be falsifiable.

Arthur : /* Empirical research */

2021-02-05T07:31:22Z

Empirical research

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	== Empirical research ==		== Empirical research ==
	According to Raymond Boudon, "quantitative surveys are those that collect comparable information on a set of elements from one element to another. It is this compatibility of information that then allows the enumeration and more generally the quantitative analysis of the data.<ref>R. Boudon; Les méthodes en sociologie, p.31 </ref>.		According to Raymond Boudon, "quantitative surveys are those that collect comparable information on a set of elements from one element to another. It is this compatibility of information that then allows the enumeration and more generally the quantitative analysis of the data.<ref>R. Boudon; Les méthodes en sociologie, p.31 </ref>

	Empirical research must develop within a framework that is collectively shared. It is a process where research is collective, because it is based on a process produced by others, the process must also be public with the idea of transparency that is important in research. Everything must be transparent, controllable by others. All the procedures implemented must be controllable by others with the idea of replicating what has been done, everything must be replicable. Research is a collective and public process that must be subject to criteria of transparency and control.		Empirical research must develop within a framework that is collectively shared. It is a process where research is collective, because it is based on a process produced by others, the process must also be public with the idea of transparency that is important in research. Everything must be transparent, controllable by others. All the procedures implemented must be controllable by others with the idea of replicating what has been done, everything must be replicable. Research is a collective and public process that must be subject to criteria of transparency and control.
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	*in the choice of technical instruments used.		*in the choice of technical instruments used.

	~~It is at~~ these two moments ~~that~~ the collective research frame of reference is seen, expressed and found.		At these two moments, the collective research frame of reference is seen, expressed and found.

	== The five phases of the process and the research question ==		== The five phases of the process and the research question ==

Arthur le 14 février 2019 à 23:01

2019-02-14T23:01:32Z

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	\| fr = De la théorie aux données		\| fr = De la théorie aux données
	\| es = De la teoría a los datos		\| es = De la teoría a los datos
			\| it = Dalla teoria ai dati
	}}		}}

Arthur le 24 janvier 2019 à 19:35

2019-01-24T19:35:53Z

← Version précédente		Version du 24 janvier 2019 à 21:35
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	{{Translations		{{Translations
	\| fr = De la théorie aux données		\| fr = De la théorie aux données
			\| es = De la teoría a los datos
	}}		}}

Arthur le 1 avril 2018 à 18:37

2018-04-01T18:37:15Z

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			{{Infobox Lecture
			\| image =
			\| image_caption =
			\| faculté = [[Faculté des sciences de la société]]
			\| département = [[Département de science politique et relations internationales]]
			\| professeurs = [[Marco Giugni]]<ref>[https://unige.ch/sciences-societe/speri/membres/marco-giugni/ Page personnelle de Marco Giugni sur le site de l'Université de Genève]</ref>
			\| assistants =
			\| enregistrement =
			\| cours = [[Introduction to the methods of political science]]
			\| lectures =
			* [[Introductory course on the methods of political science]]
			* [[The positivist paradigm and the interpretative paradigm]]
			* [[Fundamental scientific methods]]
			* [[From theory to data]]
			* [[Data collection]]
			* [[The processing of data]]
			}}

	When we do research and in particular quantitative research, that is, research that is part of the post-positive paradigm, operationalization is the key moment in the process. Without a good operationalization, one cannot make a relevant research, because it is a formalized structure.		When we do research and in particular quantitative research, that is, research that is part of the post-positive paradigm, operationalization is the key moment in the process. Without a good operationalization, one cannot make a relevant research, because it is a formalized structure.

Arthur le 1 avril 2018 à 18:33

2018-04-01T18:33:38Z

← Version précédente		Version du 1 avril 2018 à 20:33
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	When we do research and in particular quantitative research, that is, research that is part of the post-positive paradigm, operationalization is the key moment in the process. Without a good operationalization, one cannot make a relevant research, because it is a formalized structure.		When we do research and in particular quantitative research, that is, research that is part of the post-positive paradigm, operationalization is the key moment in the process. Without a good operationalization, one cannot make a relevant research, because it is a formalized structure.

			{{Translations
			\| fr = De la théorie aux données
			}}

	= Scientific Research =		= Scientific Research =

Arthur le 1 avril 2018 à 18:28

2018-04-01T18:28:43Z

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	6) '''Results'''		6) '''Results'''

	→ '''induction''': we go up to the generality and we come back on the theory; connected by a method of ~~feedbacks~~ to the theory passing from the particular to the general through the results. There is the idea that the results will be used to create theories and analyze hypotheses.		→ '''induction''': we go up to the generality and we come back on the theory; connected by a method of feedback to the theory passing from the particular to the general through the results. There is the idea that the results will be used to create theories and analyze hypotheses.

	In the reality of research, the steps are often distributed in a different way; often assumptions are developed after the data have been collected. Sometimes the theory is developed after having analysed the data, sometimes during the empirical phase, sometimes the theme is new and unknown that is why a purely descriptive research is made, sometimes the data collections do not start from a specific theory, because we want to include a wider field that allows to analyze several hypotheses.		In the reality of research, the steps are often distributed in a different way; often assumptions are developed after the data have been collected. Sometimes the theory is developed after having analysed the data, sometimes during the empirical phase, sometimes the theme is new and unknown that is why a purely descriptive research is made, sometimes the data collections do not start from a specific theory, because we want to include a wider field that allows to analyze several hypotheses.

Arthur : /* Types de variables */

2018-04-01T18:27:16Z

Types de variables

← Version précédente		Version du 1 avril 2018 à 20:27
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	*I'''ndividual / collective''' (aggregate, global, contextual)		*I'''ndividual / collective''' (aggregate, global, contextual)
	*'''Value processing''': this is the most important aspect, it is related to measurement. There are different types of variables. Knowing what type of variable we have to do will tell us what type of analysis we have to do; the whole process of operationalization and the end of the process, namely the creation of variables is fundamental leading to variables of different natures.		*'''Value processing''': this is the most important aspect, it is related to measurement. There are different types of variables. Knowing what type of variable we have to do will tell us what type of analysis we have to do; the whole process of operationalization and the end of the process, namely the creation of variables is fundamental leading to variables of different natures.
	== Types de variables ==		== Types of variables ==
	~~Il y a trois~~ types de variables ~~qu’il est possible de distinguer entre quatre critères~~		There are three types of variables that can be distinguished between four criteria

	{\| cellspacing="0" cellpadding="20" border="1"		{\| cellspacing="0" cellpadding="20" border="1"
	!		!
	!~~nominales~~		!nominal
	!ordinales		!ordinales
	!cardinales		!cardinales
	\|-		\|-
	\|'''~~États de propriétés~~ : ~~les valeurs de la~~ variable'''		\|'''Property states: the values of the variable'''
	\|		\|
	~~Catégories~~ non ~~ordonnés et non ordonnables~~.		Non-ordered and non-ordinable categories.

	ex : ~~nationalité~~, religion		ex : nationality, religion
	\|		\|
	~~Aussi catégorielles~~, ~~mais ordonnées~~ ; ~~on peut créer un ordre~~.		Also categorical, but ordered; one can create an order.

	~~ex : niveau éducation~~, ~~dans quelle mesure s'intéresse-t-on à quelque chose~~.		e.g. education level, to what extent are we interested in something.
	\|		\|
	~~Plus des catégories~~, ~~mais des~~ variables :		More categories, but variables :
	*'''~~continues~~''' - ex : ~~âge~~ = 1 an, ~~un mois~~, 3 ~~heures~~),		*'''continue''' - ex : age = 1 year, 1 month, 3 hours),
	*'''~~discrètes~~''' - ex : 1, 2, ~~enfants~~, ~~pas demi enfant~~ !		*'''discreet''' - ex: 1, 2, children, not half child!
	\|-		\|-
	\|'''~~Procédure d'opérationnalisation~~'''		\|'''Operationalization procedure'''
	\|		\|
	~~Logique de classification~~.		Classification logic.
	\|		\|
	~~On peut les mettre dans un~~ certain ~~ordre~~. ~~On peut les inclure dans des catégories différentes~~. ~~Il y a un~~ ordonnénement, la variable ~~ordinale résulte de la définition opératoire qui consiste à donner un ordre aux différents objets~~.		We can put them in a certain order. They can be included in different categories. There is an ordonnénement, the ordinal variable results from the operative definition which consists in giving an order to the various objects.
	\|		\|
	*'''~~Mesuration~~''' :		*'''Measurement''' :
	~~intervalle entre eux est le même~~ (1 an, ~~par exemple~~) -v. ~~continues~~-		interval between them is the same (1 year, for example) -v. continuous-
	*'''~~Comptage~~''' :		*'''Counting''' :
	~~on peut les compter~~ -v. ~~discrètes~~-		we can count them -v. discreet-
	\|-		\|-
	\|'''~~Caractéristiques de valeurs~~'''		\|'''Value Characteristics'''
	\|		\|
	~~La caractéristique des valeurs est des noms~~.		The characteristic of values is names.

	ex : ~~canadien~~, ~~suisse~~		ex : Canadian, Swiss

	~~Les catégories doivent être exhaustives~~. ~~Toutes les catégories doivent être contemplées et mutuellement exclusives~~.		The categories must be exhaustive. All categories must be contemplated and mutually exclusive.
	\|		\|
	~~Nombre avec propriétés ordinales~~.		Number with ordinal properties.

	ex : ~~peu~~, ~~assez~~, ~~très~~ ; ~~on associe un chiffre à chaque état~~, ce code ~~est arbitraire~~.		ex: little, enough, very; we associate a number to each state, this code is arbitrary.
	\|		\|
	~~Nombre avec propriétés cardinales~~, ~~le nombre reflète une propriété réelle~~.		Number with cardinal properties, the number reflects a real property.

	ex : ~~allé voter~~ 5 ~~fois~~, ~~on ne peut pas associer des chiffres arbitrairement~~.		ex: went to vote 5 times, one cannot arbitrarily associate figures.
	\|-		\|-
	\|'''~~Opérations effectuables sur les valeurs~~'''		\|'''Operations that can be carried out on securities'''
	\|		\|
	~~Egalite ou inégalité~~.		Equality or inequality.

	ex : ~~musulman diffèrent de catholique~~		ex: Muslim differs from Catholic
	\|		\|
	~~Egalite ou inégalité~~, ~~ordre supérieur ou inférieur~~.		Equality or inequality, higher or lower order.
	\|		\|
	~~On peut appliquer toutes les opérations mathématiques~~, ~~équivalences~~, ~~différences~~, multiplication, etc.		All mathematical operations, equivalences, differences, multiplication, etc. can be applied.

	ex : ~~un individu de~~ 40 ~~ans est deux fois un individu de~~ 20 ~~ans~~.		ex: a 40-year-old is twice a 20-year-old.
	\|}		\|}

Arthur : /* Criteria for distinguishing variables */

2018-04-01T18:23:06Z

Criteria for distinguishing variables

← Version précédente		Version du 1 avril 2018 à 20:23
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	== Criteria for distinguishing variables ==		== Criteria for distinguishing variables ==
	La variable ~~est un~~ concept ~~opérationnalisé~~ ; ~~il y a plusieurs manières de définir les~~ variables ~~et donc plusieurs manières de les classer~~ :		The variable is an operationalized concept; there are several ways to define variables and therefore several ways to classify them:

	*'''non-~~manipulables~~ / ~~manipulables~~''' :		*'''non-manipulable / manipulable''':
	**'''non-manipulable''' : ~~ce sont des~~ variables ~~qu’on ne peut modifier par exemple les caractéristiques sociodémographiques~~.		**'''non-manipulable''': these are variables that cannot be modified, for example, socio-demographic characteristics.
	**'''manipulable''' : ~~les~~ questions ~~à se poser~~.		**'''manipulable''': the questions to ask.

	*'''~~dépendantes~~ / ~~indépendantes~~''' :		*'''dependent / independent''':
	**'''~~dépendantes~~''' : variables ~~expliquées~~ ; ~~c’est ce que l’on veut expliquer aussi appelé~~ variable ~~endogène~~.		**'''dependent''': variables explained; this is what we want to explain also called endogenous variable.
	**'''~~indépendantes~~''' : variables ~~explicatives~~ ; ~~elle est censée d'expliquer aussi appelée~~ variable ~~exogène~~.		**'''independent''': explanatory variables; it is supposed to explain also called exogenous variable.

	*'''~~non-observées~~ (~~latentes~~) / ~~observées~~ (~~manifestes~~)''' :		*'''unobserved (latent) / observed (manifest)''':
	**'''~~non-observées~~''' : ~~les valeurs sont des~~ variables ~~latentes non-observables~~.		**'''unobserved''': values are unobservable latent variables.
	**'''~~observés~~''' : ~~les~~ opinions ~~peuvent être par exemple observées~~.		**'''observed''': opinions can be observed, for example.

	Nota bene : ~~quand~~ on ~~travaille sur les valeurs en~~ science-~~politique on aborde les attitudes ; à travers on va remonter à quelque chose de non-observable~~.		Nota bene : when we work on values in science-politics we approach attitudes through we go back to something unobservable.

	*'''~~Individuelles~~ / ~~collectives~~''' (~~agrégées~~, ~~globales~~, ~~contextuelles~~)		*I'''ndividual / collective''' (aggregate, global, contextual)
			*'''Value processing''': this is the most important aspect, it is related to measurement. There are different types of variables. Knowing what type of variable we have to do will tell us what type of analysis we have to do; the whole process of operationalization and the end of the process, namely the creation of variables is fundamental leading to variables of different natures.
	*'''~~Traitement des valeurs~~''' : ~~c'est l'~~aspect ~~le plus important~~, ~~il est lié à la mesuration~~. ~~Il existe différents~~ types de variables. ~~Savoir à quel~~ type de variable ~~on a à faire va nous dire à quel~~ type ~~d’analyse on a à faire~~ ; ~~tout le processus d’opérationnalisation et la fin du processus à savoir la création de~~ variables ~~est fondamental débouchant sur des~~ variables de natures ~~différentes~~.

	== Types de variables ==		== Types de variables ==
	Il y a trois types de variables qu’il est possible de distinguer entre quatre critères		Il y a trois types de variables qu’il est possible de distinguer entre quatre critères

Arthur : /* Errors in the transition from concepts to indicators */

2018-04-01T18:20:25Z

Errors in the transition from concepts to indicators

← Version précédente		Version du 1 avril 2018 à 20:20
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	To know if it is a good operationalization, a choice must be justified, that is, it must meet a criterion of objectivity and justification without eliminating arbitrariness.		To know if it is a good operationalization, a choice must be justified, that is, it must meet a criterion of objectivity and justification without eliminating arbitrariness.

	== ~~Critères de distinction des~~ variables ==		== Criteria for distinguishing variables ==
	La variable est un concept opérationnalisé ; il y a plusieurs manières de définir les variables et donc plusieurs manières de les classer :		La variable est un concept opérationnalisé ; il y a plusieurs manières de définir les variables et donc plusieurs manières de les classer :

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	There can be different types of errors resulting from a distinction between two phases:		There can be different types of errors resulting from a distinction between two phases:

	1) '''phase ~~d'indication~~''' : ~~théorique~~		1) '''indication phase''': theoretical

	~~On peut distinguer deux~~ types ~~d'erreurs~~ :		Two types of errors can be distinguished:
	*'''~~d'indication~~''' : ~~dû à un mauvais choix des indicateurs~~, ~~l’indicateur ne mesure pas ce qu’il est censé mesurer~~. ~~C’est une erreur qui est presque par définition constante ou systématique~~, ~~difficilement détectable sinon à travers le raisonnement logique et l’intuition~~. ~~Dans ce cas il y~~ a ~~un problème de validité de l’indicateur c’est-à-dire qu’il ne mesure pas vraiment le~~ concept ~~qu’il est censé mesurer~~.		*'''Indicator''': Due to poor indicator selection, the indicator does not measure what it is intended to measure. It is an error that is almost by definition constant or systematic, difficult to detect except through logical reasoning and intuition. In this case there is a problem with the validity of the indicator, i.e. it does not really measure the concept it is supposed to measure.
	*'''~~systématique~~''' : ~~une fois mal fait~~, ~~cela va se répercuter sur la recherche~~.		*'''systematic''': once done wrong, it will have repercussions on research.

	2) '''phase ~~empirique~~''' : ~~erreur opérationnalisation~~		2) '''empirical phase''': operationalization error These errors can result from operationalization errors, they can be systematic or accidental. We can distinguish three sources of operationalization errors, in other words there are three moments at which we are subject to danger and risk of falling into these errors. However we will ignore the data processing error.
	~~Ces erreurs peuvent découler d’erreurs d’opérationnalisations~~, ~~elles peuvent être systématiques ou accidentelles~~. ~~On peut distinguer trois~~ sources ~~d’erreurs d’opérationnalisation~~, ~~en d’autres termes il y a trois~~ moments ~~auxquels on est soumis au~~ danger ~~et au risque de tomber dans ces erreurs~~. ~~Toutefois nous allons ignorer l’erreur de traitement des données~~.		*'''case selection''': badly chosen cases, there may be errors.
	*'''~~sélection des cas~~''' : ~~cas mal choisis~~, ~~il peut y avoir des erreurs~~.		**'''coverage''': consists of the fact that we did not cover the population we wanted to cover.
	**'''~~couverture~~''' : ~~consiste du fait qu'on n'ait pas couvert la~~ population ~~qu'on voulait couvrir~~.		**'''sampling''': if the sample is taken according to certain procedures, the percentage of error can be calculated.
	**'''~~échantillonnage~~''' : ~~si l'échantillon est fait selon certaines procédures on peut calculer le pourcentage d'erreur~~.		**'''non-response''': there are individuals who do not wish to respond to the survey, which will bias the analysis.
	**'''non-~~réponse~~''' : ~~il y a des individus qui ne souhaitent pas répondre au sondage ce qui va biaiser l’analyse~~.

	~~Il y plusieurs~~ sources ~~d’erreurs liées à la sélection des sujets dans une première~~ phase ~~qui est aussi une erreur d’opérationnalisation~~.		There are several sources of errors related to the selection of subjects in a first phase which is also an operationalization error.

	*'''d'observation''' : ~~mauvaise~~ observation ~~des cas~~		*'''observation''': poor observation of cases
	**'''interviewer''' : ~~erreurs liées à l’interviewer~~, ~~il pourrait soumettre l’interviewé à des pressions directes ou indirectes~~.		**'''interviewer''': errors linked to the interviewer, he/she could subject the interviewee to direct or indirect pressure.
	**'''~~interviewé~~''' : ~~la personne peut mal comprendre la~~ question ~~ou volontairement biaiser la recherche~~.		**'''interviewee''': the person may misunderstand the question or deliberately bias the research.
	**'''instrument''' : ~~la manière dont est administrée la question~~.		**'''instrument''': the manner in which the issue is administered.
	**'''mode ~~de traitement des données~~''' : ~~analyser d’une mauvaise manière~~.		**'''data processing mode''': analyse in the wrong way.

	There can be errors that make the initial concept no longer correspond or only partly correspond with the final concept which is the variable. To do this, we must be aware and put in place everything possible to reduce the time lag as much as possible. Note that the only type of error that can be measured is sampling error.		There can be errors that make the initial concept no longer correspond or only partly correspond with the final concept which is the variable. To do this, we must be aware and put in place everything possible to reduce the time lag as much as possible. Note that the only type of error that can be measured is sampling error.

From theory to data - Historique des versions

Arthur : /* Criteria for the Scientificity of Assumptions */

Arthur : /* Empirical research */