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Record W7039755504

Mediation and Regulation : Between Counterculture and New Way of Exerting Power

2015· article· fr· W7039755504 on OpenAlexaboutno aff

Bibliographic record

VenueORBi (University of Liège) · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsnot available
Fundersnot available
KeywordsCounterculturePower (physics)MediationContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Dans un contexte contemporain de modification de la régulation de l’espace public (montée en puissance des intermédiaires, des dispositifs, des instruments d’action publique…), les mutations sociales apparaissent comme faisant la part belle tantôt au pluralisme normatif et à l’horizontalisation des structures (Kuty et al., 2012), tantôt à la montée du néolibéralisme et de ses principes individualisants d’employabilité, de concurrence et d’efficacité (Courpasson, 2000 ; Laval et al., 2012). Idéologie présentée comme un nouveau mode de régulation sociale (Bonafé-Schmitt, 1996) reposant sur la responsabilité et l’autonomie des participants aidés par un tiers neutre (Guillaume-Hofnung, 1995), la médiation est notamment devenue un concept caractérisant de nouveaux intermédiaires de l’action publique (Verhoeven, 2012). Basée sur un matériau empirique issu d’une recherche doctorale portant sur la médiation en milieu scolaire, cette contribution interrogera l’évolution et l’identité de deux services de médiation scolaire en Belgique francophone, marqués par une tension sous-jacente : dans un contexte scolaire multimodal et complexe (Maroy, 2008), accroché à un programme institutionnel pourtant en déclin (Dubet, 2010), les médiateurs sont-ils représentatifs d’une contre-culture ou d’un nouveau mode d’exercice du pouvoir ?

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0060.059
Scholarly communication0.0140.006
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.041
GPT teacher head0.243
Teacher spread0.201 · 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 designTheoretical or conceptual
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
Published2015
Admission routes1
Has abstractyes

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