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Record W2789770964 · doi:10.3917/pox.120.0061

Les enseignements d’une comparaison manquée. Les professionnels de la participation en France et au Québec

2018· article· fr· W2789770964 on OpenAlexaboutno aff
Alice Mazeaud, Magali Nonjon

Bibliographic record

VenuePolitix · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceESPACEArt

Abstract

fetched live from OpenAlex

Cet article procède à une auto-analyse d’une expérience de comparaison manquée des professionnels de la participation en France et au Québec. Les difficultés rencontrées soulignent que les circulations croisées de dispositifs participatifs et d’acteurs entre ces deux espaces ne facilitent pas la comparaison. Au contraire, elles font obstacle à l’analyse en donnant l’illusion du partage d’un même univers de sens et de pratiques. À ce titre, elles rappellent que les catégories de l’analyse comparative ne sont jamais données. Elles sont à construire, à travers une comparaison compréhensive, sensible aux significations et aux institutions nationales. Une telle démarche semble ici d’autant plus cruciale à adopter que les chercheurs ne sont pas extérieurs à l’espace de la participation, ils en sont même des acteurs de premier plan. Aussi, même si l’objectif comparatif n’a pas été atteint, notre expérience s’est avérée particulièrement féconde pour mieux comprendre notre terrain français. Le passage par le Québec nous a permis de voir et d’interroger des éléments que nous ne percevions pas ou plus.

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)0.007
metaresearch head score (Gemma)0.013
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 score0.126
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0120.006
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.301
GPT teacher head0.539
Teacher spread0.238 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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