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Record W4403010626 · doi:10.7202/1113757ar

Dynamique et structure du marché de l’emploi universitaire québécois dans les disciplines des sciences sociales, 1900-2020

2024· article· fr· W4403010626 on OpenAlexaffvenueabout
Mahdi Khelfaoui, Yves Gingras

Bibliographic record

VenueRecherches sociographiques · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPolitical scienceSociology

Abstract

fetched live from OpenAlex

Cet article analyse les embauches des professeurs d’université dans le champ des sciences sociales au Québec (principalement en sociologie, science politique, économie, géographie, anthropologie, communication, psychologie/psychoéducation et travail social) entre 1900 et 2020. Nous montrons que la langue d’enseignement (français ou anglais), la position géographique (métropoles ou régions) de l’université d’embauche et le prestige perçu des universités d’obtention du doctorat et d’embauche constituent autant de facteurs contribuant à la structuration du marché de l’emploi universitaire québécois en sciences sociales. Nous mettons au jour un mouvement historique de « québécisation » des embauches, analogue au mouvement de « canadianisation » observé dans le reste du Canada, qui a débuté à la fin des années 1960, atteint son apogée à la fin des années 1990, et connu ensuite un recul au tournant du 21 e siècle dans le contexte des discours sur l’internationalisation des universités. Nous montrons finalement l’existence d’une féminisation des corps professoraux qui, pour être différenciée selon les disciplines, est continuelle depuis la fin des années 1960.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0020.009
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.110
GPT teacher head0.381
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes3
Has abstractyes

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