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Record W4412909391 · doi:10.54932/dbmw8840

Fais comme ta sœur : reste à l’école !

2025· report· fr· W4412909391 on OpenAlexaboutno aff
Fabian Lange, Marie Connolly

Bibliographic record

Venuenot available
Typereport
Languagefr
FieldSocial Sciences
TopicSocial Policies and Family
Canadian institutionsnot available
Fundersnot available
KeywordsArtGeologyPhilosophyHumanitiesMathematics

Abstract

fetched live from OpenAlex

Malgré de vastes progrès en matière de scolarisation au cours des dernières décennies, le Québec continue de faire piètre figure en matière de décrochage scolaire, particulièrement chez les garçons. En 2021, 234 000 hommes n’avaient pas de diplôme d’études secondaires. Chez les 25 à 34 ans, 12 % n’avaient aucun diplôme ni aucune qualification, soit la pire performance de toutes les provinces canadiennes. Cette sous-scolarisation des garçons représente une perte substantielle de potentiel de productivité. Une étude CIRANO (Connolly et Lange, 2025) montre que si on s’attaquait au problème et que les garçons réussissaient à atteindre le même taux de décrochage que celui des filles, il en résulterait des gains importants pour eux et pour toute la société. D’ici 20, 30 ou 40 ans, le nombre d’hommes sans diplôme sur le marché du travail pourrait diminuer de moitié.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.568
Threshold uncertainty score0.868

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 studies0.0100.003
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0520.008

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 head0.130
GPT teacher head0.382
Teacher spread0.252 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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