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Record W2223680017 · doi:10.1177/216507990605400603

Promoting Personal Safety of Building Service Workers

2006· article· en· W2223680017 on OpenAlexaffabout
Shelley I Chen, D. Lynn Skillen

Bibliographic record

VenueAAOHN Journal · 2006
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsAlberta Emerald Foundation
Fundersnot available
KeywordsPersonal protective equipmentDescriptive statisticsPsychosocialPromotion (chess)Service (business)PsychologyMedical educationBusinessNursingMedicineMarketingCoronavirus disease 2019 (COVID-19)Political science

Abstract

fetched live from OpenAlex

This exploratory, descriptive study conducted at a large western Canadian university solicited perceptions of personal safety among building service workers who perform night shift work alone. Ten semi-structured interviews were conducted at approximately 10:00 p.m. or 7:00 a.m with a convenience sample of night building service workers in private or semi-private locations on the university campus. Transcribed interview data were subjected to inductive content analysis using descriptive, interpretive, and pattern coding (Miles & Huberman, 1994). Results suggest that building service night shift workers are exposed to personal safety hazards in their physical and psychosocial work environments. In addition, culturally and linguistically appropriate delivery of safety training and education about policies and procedures is required for culturally diverse building service workers. Promotion of personal safety in this heterogeneous worker population requires due diligence, assessment, and advocacy.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.407

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.447
Teacher spread0.384 · 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 designObservational
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

Citations8
Published2006
Admission routes2
Has abstractyes

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