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Record W107394683 · doi:10.3233/wor-2008-00692

Work organization and health: A qualitative study of the perceptions of workers

2008· article· en· W107394683 on OpenAlexaff
Joy C. MacDermid, Sybil Geldart, Renee Williams, Muriel G. Westmorland, Chia-Yu A. Lin, Harry S. Shannon

Bibliographic record

VenueWork · 2008
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsInstitute for Work & HealthWilfrid Laurier UniversityMcMaster UniversityHand and Upper Limb Clinic
Fundersnot available
KeywordsWork (physics)Focus groupQualitative researchPerceptionPsychologyWork environmentPublic relationsSociologySocial psychologyJob satisfactionBusinessMarketingPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Workplaces comprise a large component of life partcipation. The complexity of work organization makes it challenging to understand how the environment impacts the health of workers and who is responsible for creating a healthy workplace. This investigation sought to understand the views of workers about workplace health. A qualitative approach was used to gain understanding of workers' experiences of how work organization (WO) impacts their health and needs to change. Four individual interviews and 7 focus groups with workers were conducted. Data were thematically analyzed. Findings comprised two common themes: 1. The need for support and respect in the work place; and 2. The need for organizational commitment to safe work practices and healthy work environments. Findings suggest workers want and need to be involved in creating a healthy workplace. Opportunities to involve workers more in workplace health are discussed.

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)0.012
metaresearch head score (Gemma)0.015
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 score0.016
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0110.007
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.183
GPT teacher head0.531
Teacher spread0.349 · 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

Citations20
Published2008
Admission routes1
Has abstractyes

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