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Record W2935689003 · doi:10.3917/mouv.097.0083

Le « printemps érable » et la lutte étudiante contre la discipline de l’endettement

2019· article· fr· W2935689003 on OpenAlexaboutno aff
Jean‐François Bissonnette

Bibliographic record

VenueMouvements · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

L’annonce de l’augmentation des frais de scolarité universitaires par le gouvernement provincial du Québec a provoqué une lutte étudiante massive. Les étudiant·es en grève, dénommé·es « carrés rouges » en référence au carré de feutre rouge épinglé à leur boutonnière, symbolisant le refus de devoir plonger « carrément dans le rouge » pour pouvoir étudier, ont dénoncé non seulement la hausse des frais d’inscription, mais aussi le système d’endettement individuel adossé à cette mesure. La décision gouvernementale inversait en effet l’équation progressiste : ce n’était plus à la collectivité d’assurer l’essentiel des coûts associés à l’enseignement supérieur, la société toute entière gagnant à compter sur des citoyen·es éclairé·es. C’était désormais les diplômé·es qui, à titre individuel, apparaissaient comme les bénéficiaires de leur formation et se devaient alors de la financer directement. Par leur lutte victorieuse, les « carrés rouges » ont ainsi rejeté la vision du monde faisant du crédit l’instrument privilégié de tout projet de vie et de l’éducation une forme d’investissement financier.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.949
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0190.025
Scholarly communication0.0150.005
Open science0.0020.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0220.003

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 head0.014
GPT teacher head0.315
Teacher spread0.301 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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