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Record W2466289317 · doi:10.1093/occmed/kqw082

Awareness of occupational skin disease in the service sector

2016· article· en· W2466289317 on OpenAlexafffund
D. Linn Holness, Irena Kudla, Jacqueline T. Brown, S.C. Miller

Bibliographic record

VenueOccupational Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsWorkplace Health, Safety and Compensation CommissionOccupational Cancer Research CentrePublic Health OntarioUniversity of TorontoSt. Michael's Hospital
FundersWorkplace Safety and Insurance Board
KeywordsBusinessFocus groupService (business)Tertiary sector of the economyTourismWork (physics)Environmental healthMarketingMedicinePublic relationsEngineeringPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Occupational skin disease (OSD) is a common occupational disease. Although primary prevention strategies are known, OSDs remain prevalent in a variety of work environments including the service sector (restaurant/food services, retail/wholesale, tourism/hospitality and vehicle sales and service). AIMS: To obtain information about awareness and prevention of OSD in the service sector. METHODS: Focus groups and a survey were conducted with two groups. The first consisted of staff of the provincial health and safety association for the service sector and the second group comprised representatives from sector employers. Focus groups highlighted key issues to inform the survey that obtained information about perceptions of awareness and prevention of OSD and barriers to awareness and prevention. RESULTS: Both provincial health and safety association staff and sector employer representatives highlighted low awareness and a low level of knowledge of OSD in the sector. Barriers to awareness and prevention included a low reported incidence of OSD, low priority, lack of training materials, lack of time and cost of training, lack of management support and workplace culture. CONCLUSIONS: A starting point for improving prevention of OSD in the service sector is increased awareness. Identification of the barriers to awareness and prevention will help to shape an awareness campaign and prevention strategies. Building on existing experience in Europe will be important.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.048
GPT teacher head0.334
Teacher spread0.286 · 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 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

Citations9
Published2016
Admission routes2
Has abstractyes

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