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Record W2906501904 · doi:10.4000/books.pum.13413

32. Un débat sur la démocratisation de l'enseignement

2000· book-chapter· fr· W2906501904 on OpenAlexaboutno aff
Institut canadien des affaires publiques, Tremblay Arthur, Gérin-Lajoie Paul, Falardeau Jean-Charles, Guindon Léo

Bibliographic record

VenuePresses de l’Université de Montréal eBooks · 2000
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

À compter de 1953, l’Institut canadien des affaires publiques (ICAP) est à la fois un rassemblement d’esprits réformistes et progressistes et un lieu de débats structurés sur les différents enjeux confrontant la société québécoise. Ainsi, annuellement, l’ICAP tient une conférence sur un thème donné. Cette conférence prend la forme d’une « retraite fermée » dans un hôtel de villégiature des Laurentides. Cent cinquante ou deux cents personnes, pendant quatre jours, écoutent des conférenciers prestigieux ou débattent entre elles du thème choisi. Les conférences et les résumés des débats sont éventuellement publiés. Ces rencontres annuelles sont l’occasion d’échanges et de discussions et permettent de développer, sinon des consensus, du moins un discours critique réformiste largement partagé sur un problème ou l’autre de la société québécoise. L’ICAP permet surtout un réseautage intellectuel et politique qui rejoint des membres influents de divers milieux québécois, réseautage qui accroît l’influence de certaines idées réformistes dans la société. En 1956, la conférence de l’ICAP porte sur la question de la démocratisation de l’éducation. Quelques interventions mettent en lumière le sens, les conditions et la portée d’une telle démocratisation.

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: Other · Consensus signal: Other
Teacher disagreement score0.949
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0140.009
Scholarly communication0.0090.005
Open science0.0010.003
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0330.004

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 head0.041
GPT teacher head0.270
Teacher spread0.229 · 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
Published2000
Admission routes1
Has abstractyes

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