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Record W4311990938 · doi:10.3917/risa.884.0921

Du tournant participatif des administrations à la bureaucratisation de la démocratie participative. Étude à partir du cas français.

2022· article· fr· W4311990938 on OpenAlexaff
Alice Mazeaud, Guillaume Gourgues, Magali Nonjon

Bibliographic record

VenueRevue Internationale des Sciences Administratives · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsPolitical scienceHumanitiesPublicsPhilosophy

Abstract

fetched live from OpenAlex

Cet article se propose de contribuer à la réflexion sur le tournant participatif de l’action publique et de l’administration en étudiant le profil et le travail des agents publics spécialisés dans la participation citoyenne au sein des administrations locales françaises. A rebours des discours qui promeuvent la modernisation participative de l’administration, l’analyse de l’activité quotidienne des agents publics en charge de la participation permet de saisir les dynamiques de bureaucratisation de la participation citoyenne. Faute de bouleverser les routines administratives, les agents spécialisés inventent de nouvelles routines essentiellement destinées à maintenir en place des dispositifs, même lorsque ces derniers n’ont peu ou pas d’effet sur la conduite de l’action publique. Remarques à l’intention des praticiens Cet article éclaire les processus de mise en administration de la participation citoyenne qui s’opère en France selon une double logique de spécialisation et de diffusion, et analyse les aspects concrets du travail participatif dans les administrations.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.715

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0110.010
Scholarly communication0.0090.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.110
GPT teacher head0.360
Teacher spread0.250 · 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 designObservational
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

Citations2
Published2022
Admission routes1
Has abstractyes

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