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Record W2685312225 · doi:10.7202/1039933ar

Notre maître l’avenir, ou le terreau des ancêtres? L’ambivalence temporelle chez Fernand Dumont (1956-1967)

2017· article· fr· W2685312225 on OpenAlexaffvenueabout
Daniel Poitras

Bibliographic record

VenueRecherches sociographiques · 2017
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Au tournant des années 1960, Fernand Dumont se penche sur le passé du Québec et constate les ravages provoqués par le fatalisme et la « Grande-Peur québécoisée », qui atrophient l’expérience du passé. Le jeune sociologue attend de l’historien qu’il libère ses contemporains des fixations sur les mythes désuets et effectue une transmutation des valeurs anciennes en valeurs nouvelles. Plutôt que d’étudier le rôle que Dumont donne à l’historien à travers le seul récit émancipatoire du Québec, je propose d’insérer ce récit dans le régime d’historicité pour mieux saisir la transformation du rapport à l’historiographie et à l’actualisation du passé chez Dumont. Si la question des traditions à retrouver (ou carrément à donner) au Québec pour le sortir de ses ornières mobilise toute sa génération intellectuelle, Dumont manifeste une ambivalence temporelle qui le fait osciller entre le futurisme et l’appel aux ancêtres. En commentant sévèrement les historiens canadiens-français et en puisant sans vergogne dans l’histoire française, Dumont cherche à retrouver tantôt un « cheminement de la liberté », tantôt une « tradition socialiste » propres au Canada français, mais il constate à tout moment la fragilité et l’évanescence de ces repères passés, ce qui l’amène à puiser dans l’histoire française. Mais le volontarisme historiographique des années 1960 sera-t-il suffisant pour combler ce fossé et donner aux contemporains des lieux de mémoire inspirants?

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)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.900
Threshold uncertainty score0.347

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0260.023
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.199
GPT teacher head0.337
Teacher spread0.138 · 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
GenreOther

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
Published2017
Admission routes3
Has abstractyes

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