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Record W4404417602 · doi:10.1017/s0008423924000179

Le fardeau administratif dans tous ses états : Saisir les interactions entre les individus et les institutions publiques

2024· article· fr· W4404417602 on OpenAlexaff
Pierre‐Marc Daigneault, Samuel Defacqz, Claire Dupuy

Bibliographic record

VenueCanadian Journal of Political Science · 2024
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Résumé Le fardeau administratif renvoie au phénomène selon lequel la mise en œuvre des politiques publiques et, plus généralement, les interactions avec l’État, sont coûteuses et difficiles. Chaque personne est en effet confrontée à des coûts d'apprentissage lorsqu'elle acquiert de l'information sur les programmes et services publics, à des coûts de conformité lorsqu'elle tente de satisfaire à leurs règles, et à des coûts psychologiques (stress, etc.) lorsqu'elle interagit avec ceux-ci. Cette littérature, presque exclusivement anglophone, s'est développée à un rythme effréné. Cette synthèse critique fait le bilan de ces récents développements et propose une discussion articulée autour de trois thèmes : 1) Que sont les fardeaux administratifs et quels enjeux soulèvent-ils? ; 2) Quelles sont les sources des fardeaux? ; et 3) Quelles en sont les conséquences distributives et politiques? Des pistes de recherche future sont proposées pour chacun de ces thèmes.

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)0.011
metaresearch head score (Gemma)0.014
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 score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0120.022
Scholarly communication0.0100.006
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.168
GPT teacher head0.488
Teacher spread0.320 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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