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Record W3033376716 · doi:10.7202/1069447ar

Les mobilisations à l’épreuve de l’opacité policière en France

2020· article· fr· W3033376716 on OpenAlexvenueno aff
Magda Boutros

Bibliographic record

VenueLien social et Politiques · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Cet article analyse l’impact de l’opacité entourant l’action policière sur les mobilisations qui dénoncent les violences et discriminations policières en France. Sur la base d’une enquête qualitative de trois mobilisations contemporaines, l’article montre que les militants perçoivent l’opacité policière comme un obstacle important à l’élaboration de mobilisations, et qu’ils investissent dans la production de connaissances pour corroborer leurs dénonciations. De nombreux travaux sociologiques ont démontré que les mouvements sociaux participent à la production de connaissances, mais peu ont examiné la manière dont la production de connaissances influence à son tour la définition des causes militantes. En comparant différents modes de production des connaissances, l’enquête révèle que, selon la méthodologie de collecte des données, le matériau empirique collecté et le prisme d’analyse adopté, ceux-ci mettent en évidence différents aspects des pratiques policières, et contribuent ainsi à consolider certains cadrages du problème au détriment d’autres.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.663
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.304
GPT teacher head0.497
Teacher spread0.193 · 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 teacher head, not a consensus.

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

Citations15
Published2020
Admission routes1
Has abstractyes

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