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Record W6989991795

Comment les jeunes réinventent-ils l’engagement citoyen? Retour sur un forum d’échange franco-québécois

2023· other· fr· W6989991795 on OpenAlexaboutno aff

Bibliographic record

VenueEspaceINRS (National Institute for Scientific Research (Canada)) · 2023
Typeother
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Work (physics)Psychological interventionPublic policy
DOInot available

Abstract

fetched live from OpenAlex

Ce document vise à rendre compte des interventions ayant eu lieu lors du forum franco-québécois "Comment les jeunes réinventent-ils l’engagement citoyen?" qui s’est déroulé \nle 17 novembre 2022 à Paris. Il présente une synthèse analytique des principales idées \nqui ressortent des échanges tenus lors de cette journée. \nTout au long du document, les témoignages de jeunes engagés présents au forum sont \nvalorisés, en appui et en complément des propos de chercheurs, sans pour autant \nque nous puissions prétendre qu’ils reflètent toute la diversité des expériences \nd’engagement des jeunes du Québec et de la France.

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)0.010
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0250.009
Scholarly communication0.0090.004
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0220.002

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 head0.089
GPT teacher head0.325
Teacher spread0.236 · 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 designQualitative
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
Published2023
Admission routes1
Has abstractyes

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Same venueEspaceINRS (National Institute for Scientific Research (Canada))French-language works237,207