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Record W2168987787 · doi:10.12927/hcpap.2007.18668

Healthy Workplaces for Health Workers in Canada: Knowledge Transfer and Uptake in Policy and Practice

2007· article· en· W2168987787 on OpenAlexaffvenueabout
Judith Shamian, Fadi El‐Jardali

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsVictorian Order of Nurses
Fundersnot available
KeywordsHealth carePublic healthEquity (law)Population healthHealth policyHealth equityPublic policyBridging (networking)Political scienceSociologyLibrary scienceMedicineNursing

Abstract

fetched live from OpenAlex

The World Health Report launched the Health Workforce Decade (2006-2015), with high priority given for countries to develop effective workforce strategies including healthy workplaces for health workers. Evidence shows that healthy workplaces improve recruitment and retention, workers' health and well-being, quality of care and patient safety, organizational performance and societal outcomes. Over the past few years, healthy workplace issues in Canada have been on the agenda of many governments and employers. The purpose of this paper is to provide a progress update, using different data-collection approaches, on knowledge transfer and uptake of research evidence in policy and practice, including the next steps for the healthy workplace agenda in Canada. The objectives of this paper are (1) to summarize the current healthy workplace initiatives that are currently under way in Canada; (2) to synthesize what has been done in reality to determine how far the healthy workplace agenda has progressed from the perspectives of research, policy and practice; and (3) to outline the next steps for moving forward with the healthy workplace agenda to achieve its ultimate objectives. Some of the key questions discussed in this paper are as follows: Has the existing evidence on the benefits of healthy workplaces resulted in policy change? If so, how and to what extent? Have the existing policy initiatives resulted in healthier workplaces for healthcare workers? Are there indications that healthcare workers, particularly at the front line, are experiencing better working conditions? While there has been significant progress in bringing policy changes as a result of research evidence, our synthesis suggests that more work is needed to ensure that existing policy initiatives bring effective changes to the workplace. In this paper, we outline the next steps for research, policy and practice that are required to help the healthy workplace agenda achieve its ultimate objectives.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.346
Teacher spread0.264 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations66
Published2007
Admission routes3
Has abstractyes

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