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Record W2328336734 · doi:10.1097/hcm.0b013e31827ed7ab

Bringing Knowledge to Action in the Context of a Major Organizational Transition

2013· article· en· W2328336734 on OpenAlexaffabout
Marie‐Claire Richer, Martin Dawes, Caroline Marchionni

Bibliographic record

VenueThe Health Care Manager · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMultitudeContext (archaeology)Action (physics)Public relationsHealth careTransition (genetics)PerceptionPsychologyKnowledge managementPolitical scienceComputer science

Abstract

fetched live from OpenAlex

In the context of organizational transitions in health care institutions, the decisions taken by leaders and clinicians are informed by multiple sources and by a multitude of actors at all levels of the organization. A study was conducted in the context of a major organizational transition at the McGill University Health Centre in Montreal, Quebec, Canada. The purpose was to examine the body of literature around the notions of "evidence" in decision-making processes in health care. Key informants who had a strategic decision-making role linked to the transition activities were interviewed to explore their perceptions of the types of evidence used to support changes in the organization. Results revealed that managers and clinicians relied on multiple sources of evidence and shared similar concerns about reliability and validity of scant evidence.

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)0.058
metaresearch head score (Gemma)0.073
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 score0.058
Threshold uncertainty score0.308

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.073
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0180.057
Scholarly communication0.0250.014
Open science0.0030.019
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0010.000

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 head0.083
GPT teacher head0.449
Teacher spread0.366 · 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

Citations3
Published2013
Admission routes2
Has abstractyes

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