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Record W2320402092 · doi:10.1097/jom.0b013e31821e5a0b

Examining Factors Associated With the Length of Short-Term Disability-Free Days Among Workers With Previous Short-Term Disability Episodes

2011· article· en· W2320402092 on OpenAlexafffundabout
Carolyn S. Dewa, Min-Chi Chen, Nancy Chau, Stanley W. Dermer

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchPublic Health Agency of Canada
KeywordsMedicineTerm (time)Intellectual disabilityPsychiatryGerontologyPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study is to examine the timing of short-term disability recurrence among workers who have previously experienced a short-term disability episode. METHODS: The dataset comes from a Canadian resource sector company's 2003 to 2006 short-term disability leave and human resource datasets. The multi-year dataset consists of the records of 3593 employees who experienced at least on short-term disability episode between 2003 and 2006. RESULTS: The overall 1-year disability-free rate was 72.1% ± 1.6%. About half of workers with previous disability episodes for mental/behavioral disorders were disability free for more than 800 days. In contrast, about 50% of workers with previous disability episodes for physical disorders were disability free for more than 1300 days. CONCLUSIONS: These findings suggest the majority of workers with previous short-term disability episodes for mental/behavioral disorders remain disability free for more than 2 years. However, the duration of disability free days for these workers is half that of other workers with previous episodes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.093
GPT teacher head0.310
Teacher spread0.217 · 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

Citations4
Published2011
Admission routes3
Has abstractyes

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