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Record W7020438082

La retraite: discours, figures, lieux

2022· other· fr· W7020438082 on OpenAlexaboutno aff

Bibliographic record

VenueArchipelago (University of Quebec in Montreal) · 2022
Typeother
Languagefr
FieldArts and Humanities
TopicLiterature and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)LigneESPACENazism
DOInot available

Abstract

fetched live from OpenAlex

Ce dossier donne suite aux échanges qui ont eu lieu lors de la journée d’étude organisée par le comité étudiant Figura-Université de Montréal, tenue en ligne le 26 mars 2021. À cette époque, la situation sanitaire rendait impossible toute réunion en présentiel, obligeant chacun·e à rester chez soi, derrière son écran. Ce n’est pas sans penser à l’impératif de demeurer éloigné·e·s du monde que l’idée de réfléchir ensemble à la notion de la retraite est née. Alors qu’il aurait été possible de s’intéresser au thème de la maladie ou de la contagion pour dialoguer avec l’actualité, la notion de la retraite permettait, à notre sens, d’explorer un phénomène que nous vivions collectivement mais aussi,—et c’est là le paradoxe de la retraite—individuellement, et de l’interroger à nouveaux frais. \n \nC’est en étudiant des corpus divers—partant d’écrits philosophiques du XVIIe siècle français et allant jusqu’à la fiction contemporaine québécoise, en passant par des carnets d’architectes et le roman du XXe siècle—que ce dossier propose d’approfondir les réflexions partagées en mars 2021. On y retrouve quatre articles qui reflètent la qualité des contributions auxquelles nous avons eu droit et qui s’attachent chacun à différents aspects de la notion à l’étude, témoignant de sa richesse heuristique.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.503
Threshold uncertainty score1.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0230.034
Scholarly communication0.0100.006
Open science0.0020.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0130.002

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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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