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Record W4415522927 · doi:10.7202/1121162ar

« Un vent de panique s’est emparé de notre gouvernement »

2024· article· fr· W4415522927 on OpenAlexaffvenueabout
Tracey L. Adams

Bibliographic record

VenueSociologie et sociétés · 2024
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsWestern University
Fundersnot available
KeywordsContext (archaeology)CorporatizationBureaucracyWork (physics)

Abstract

fetched live from OpenAlex

S’appuyant sur la théorie des écologies des professions, cet article porte sur l’évolution récente des politiques touchant aux champs d’exercice des professions de la santé au Québec et en Nouvelle-Écosse. À partir d’une série d’entretiens ainsi que de l’analyse de documents d’orientation et de textes législatifs, cet article montre que les pénuries d’effectifs de santé ont entraîné l’élaboration de réformes hâtives et, selon de nombreuses parties prenantes, un moindre degré de concertation entre acteurs étatiques et organismes de réglementation professionnelle. Il convient d’interpréter les tensions qui ont surgi entre les différentes parties prenantes comme une querelle de compétence se déroulant au sein de l’écologie de la réglementation professionnelle. Les responsables d’organismes de réglementation accusent les acteurs étatiques d’empiéter sur leur compétence et de manquer de respect à leur expertise en matière de détermination des compétences de leurs membres et de gestion des risques dans l’intérêt du public. Bien que les relations entre l’État et les organismes de réglementation professionnelle semblent changer, leur collaboration se poursuit. L’issue de ces querelles de compétence n’est pas sans incidence sur les futures ententes portant sur la division du travail entre catégories de personnel de santé.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.621
Threshold uncertainty score0.763

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.022
Scholarly communication0.0090.008
Open science0.0010.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0180.002

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 head0.539
GPT teacher head0.645
Teacher spread0.107 · 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
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
Published2024
Admission routes3
Has abstractyes

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