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Record W2042559739 · doi:10.12927/hcpap.2011.22414

Opportunities Abound to Improve Mental Health and Psychological Safety in the Workplace

2011· article· en· W2042559739 on OpenAlexaffvenueabout
Ian J. Arnold, Gillian Mulvale, Kathy GermAnn, MaryAnn Baynton

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2011
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsWorkplace Health, Safety and Compensation CommissionCanadian Foundation for Healthcare ImprovementMental Health Commission of Canada
Fundersnot available
KeywordsMental healthCommissionOccupational safety and healthPublic relationsStatement (logic)Work (physics)PsychologyTracking (education)Political scienceApplied psychologyEngineeringLawPsychiatry

Abstract

fetched live from OpenAlex

This commentary provides a brief synopsis of the views expressed by the authors of the invited essay "The Business Case," Sari Sairanen, Deanna Matzanke and Doug Smeall. It then discusses the authors' views in light of the Mental Health Commission's framework for a Mental Health Strategy for Canada, titled Toward Recovery and Well-Being, and Dr. Martin Shain's two reports to the Mental Health Commission of Canada - Stress at Work, Mental Injury and the Law in Canada and Tracking the Perfect Legal Storm. The initiatives discussed in the lead paper are then compared with a 2009 consensus statement generated at a forum co-hosted by the Mental Health Commission and the Great-West Life Centre for Mental Health in the Workplace. The consensus statement reflects the recommendation of the forum's 40 participants that a Canadian national standard for psychological health and safety in the workplace should be developed.

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)0.015
metaresearch head score (Gemma)0.020
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.119
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0170.021
Scholarly communication0.0160.011
Open science0.0030.010
Research integrity0.0240.020
Insufficient payload (model declined to judge)0.0120.002

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 head0.455
GPT teacher head0.450
Teacher spread0.004 · 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
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

Citations3
Published2011
Admission routes3
Has abstractyes

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