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Chapitre 2. De l’accélération dans la justice des mineurs

2016· book-chapter· fr· W4312560925 on OpenAlexaff
Thomas Heller

Bibliographic record

VenuePresses universitaires du Septentrion eBooks · 2016
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Un sentiment partagé d’accélération traverse les nombreux témoignages des acteurs professionnels de la PJJ à propos des transformations récentes de la justice des mineurs et de leurs conséquences sur leur travail. Le concept d’accélération développé par le sociologue et philosophe Hartmut Rosa, dans sa critique de la modernité tardive, sert ici de point de référence à une analyse des formes d’accélération accompagnant ces changements, et de leurs implications plus particulièrement sur l’activité des éducateurs en milieu ouvert. Il apparaît notamment que les logiques gestionnaires inscrites dans ces transformations tendent à perturber les temporalités de l’action éducative, fragilisant son sens et sa mise en œuvre. Dans ces conditions, pour réaliser sa mission éducative, et ce conformément à un éthos professionnel exigeant, il arrive que l’éducateur n’ait pas d’autre choix que d’allonger son temps de travail ou d’en accélérer le ryhtme.L’appréhension du changement dans le champ de la justice des mineurs à l’aune du concept d’accélération définit également un contexte général dans lequel prend place et intervient cette activité singulière – objet d’étude principal de cet ouvrage – qu’est l’écriture.

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)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0070.005
Open science0.0010.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0190.003

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 head0.097
GPT teacher head0.329
Teacher spread0.232 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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