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Record W2026590232 · doi:10.1002/ajim.20634

The impact of hearing conservation programs on incidence of noise‐Induced hearing loss in Canadian workers

2008· article· en· W2026590232 on OpenAlexafffundabout
Hugh Davies, Steve Marion, Kay Teschke

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2008
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsUniversity of British Columbia
FundersWorkSafeBC
KeywordsAudiogramMedicineHearing lossAudiologyIndustrial noiseNoise (video)Auditory fatigueAudiometryIncidence (geometry)Cumulative incidenceNoise-induced hearing lossAbsolute threshold of hearingOccupational medicineEnvironmental healthNoise exposureOccupational exposureCohortInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Noise exposure remains one of the most ubiquitous of occupational hazards. Hearing conservation program legislation and the programs themselves were designed to lower risk of resulting occupational noise-induced hearing loss, but there has been no broad-based effort to assess the effectiveness of this policy. METHODS: The incidence of a 10-dB standard threshold shift was examined in a group of Canadian lumber mill workers, using annual audiogram series obtained from the Workers' Compensation Board of British Columbia for the period 1979-1996 and using Cox proportional hazard models. RESULTS: Mean cumulative noise exposure was 98.1 dB-years. The audiograms from 22,376 individuals, among whom there were 2,839 threshold shifts of 10 dB or greater (i.e., a "standard threshold shift"), were retained in multivariable analyses. After adjusting for potential confounders, continuous use of hearing protection, and initial hearing tests later in the study period, the risk for standard threshold shift was reduced by 30%. Risk increased sixfold, however, in those with the highest noise exposure. CONCLUSIONS: Hearing conservation programs may be effective in reducing overall incidence of hearing loss. In the absence of noise control at source, however, highly exposed workers remain at unnecessary risk.

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.137
GPT teacher head0.348
Teacher spread0.211 · 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.

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

Citations64
Published2008
Admission routes3
Has abstractyes

Explore more

Same venueAmerican Journal of Industrial MedicineSame topicHearing, Cochlea, Tinnitus, GeneticsFrench-language works237,207