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Record W2752254505 · doi:10.1177/0840470417705144

Leadership clinique en faveur de la santé de la population

2017· article· fr· W2752254505 on OpenAlexaffabout
Om Roy, Luc Tremblay

Bibliographic record

VenueHealthcare Management Forum · 2017
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsCanadian Nurses FoundationUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Les professionnels de la santé sont directement interpellés par le défi du système de santé québécois et canadien. La diversité et la force du leadership infirmier agissent comme un véritable levier dans la transformation du système. Cet article fait valoir l’engagement des infirmières autour du projet proposé par l’Ordre des infirmières et infirmiers du Québec (OIIQ), à la fois mobilisateur et facilitateur du changement. Fortement inspirées par l’approche LEADS du Collège canadien des leaders en santé (CCLS) 1 , les auteures ajoutent d’autres marqueurs cruciaux propres au leadership clinique infirmier, réunis sous l’acronyme de LEADERS. La présentation de résultats auprès des personnes soignées, de leur famille, des équipes de soins et des établissements, renforce la marque distinctive de ce leadership exercé sur le terrain. Des témoignages glanés auprès de leaders soutiennent la place déterminante de l’infirmière dans le réseau de la santé. Pour façonner l’avenir, les auteures misent sur les forces du leadership clinique.

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)0.017
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.708
Threshold uncertainty score0.587

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0070.004
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0280.003

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 head0.096
GPT teacher head0.486
Teacher spread0.389 · 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
Published2017
Admission routes2
Has abstractyes

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