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Record W4310734178 · doi:10.3138/jcs-2021-0013

Hegel au Québec : sur les traces d’une réception philosophique

2022· article· fr· W4310734178 on OpenAlexvenueaboutno aff
Laurent Alarie, Mohamed Amine Brahimi, Julien Vallières

Bibliographic record

VenueJournal of Canadian Studies · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyHegelianismArt

Abstract

fetched live from OpenAlex

Sur la base de matériaux de première main, entretiens avec des experts et archives personnelles sur l’enseignement universitaire, cet article retrace l’évolution de la réception de Hegel au Québec. L’article se divise en deux parties : la première cherche, dans l’enseignement de la philosophie, du tournant du 20esiècle aux années 1960, à dégager les traces de la réception de la pensée hégélienne ; la seconde évalue la présence du philosophe dans la recherche depuis cette époque jusqu’à aujourd’hui. Nous portons d’abord notre regard sur l’enseignement de la philosophie. C’est à travers des sources mineures, en marge des manuels autorisés, que nous trouvons une vie intellectuelle qui évolue malgré l’orthodoxie dominante de la pensée thomiste. L’étude de la réception de Hegel permet alors de s’interroger sur une historiographie qui tend à hypostasier la puissance tutélaire de la scolastique sur l’enseignement. La réorganisation de l’enseignement qui suit la constitution apostolique de 1931, le boum d’après-guerre et la massification de l’éducation accompagnant les nombreuses réformes des années 1960 transforment l’espace universitaire. Parmi les utilisations contemporaines, nous portons notre regard sur deux figures intellectuelles s’étant approprié le philosophe : George Di Giovanni et Michel Freitag.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.157
Threshold uncertainty score0.978

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0200.018
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.001

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 head0.105
GPT teacher head0.291
Teacher spread0.186 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2022
Admission routes2
Has abstractyes

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