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Reorganizing Care and Work

2006· article· en· W2314436971 on OpenAlexaffabout
Mélanie Lavoie‐Tremblay, Chantal Viens, Martine Leclerc, Angèle Bergevin, Linda Lefrançois, André Y. Tremblay

Bibliographic record

VenueThe Health Care Manager · 2006
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychosocialProductivityWork (physics)Health careNursingCitizen journalismBusinessPsychologyMedicineEngineeringPolitical scienceEconomicsEconomic growth

Abstract

fetched live from OpenAlex

A Montreal-area hospital implemented organizational changes to improve the psychosocial environment for patients and health care workers and enhance organizational efficiency. This article describes a participatory approach to improving the organization of care and work, an approach focused on productivity gains in an organization. Productivity gains were analyzed in 13 units of the Department of Nursing, which had introduced a series of organizational changes. Changes introduced in care and work organization led to productivity gains in all units overseen by the Nursing Directorate. A reorganization of care and work based on the psychosocial work environment and staff participation can have positive outcomes, both for employees and for the wider organization.

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)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0050.002
Open science0.0020.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.014
GPT teacher head0.339
Teacher spread0.325 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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