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Record W1620021945 · doi:10.3233/wor-2003-00322

The needs and experiences of injured workers: A participatory research study

2003· article· en· W1620021945 on OpenAlexaffabout
Bonnie Kirsh, Pat McKee

Bibliographic record

VenueWork · 2003
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsGeneral partnershipParticipatory action researchRehabilitationCompensation (psychology)Work (physics)Citizen journalismProcess (computing)PsychologyWorkers' compensationMedical educationNursingMedicinePublic relationsBusinessPhysical therapySocial psychologyPolitical scienceSociologyEngineeringFinance

Abstract

fetched live from OpenAlex

This paper reports on the findings of a participatory research study in which 290 injured workers in Ontario, Canada responded to a survey that was developed and administered by a group of university researchers in partnership with injured worker peer researchers. The objectives of the study were to gain a broad view of the needs and experiences of injured workers and to develop strategies for change. Findings indicated that many injured workers experience undue financial, emotional and physical hardship during the compensation, treatment and rehabilitation process. These hardships are experienced due to perceived lack of respect, insufficient information concerning rights and the return-to-work process, and limited opportunities for input into the medical or rehabilitation process. Recommendations for increasing the power of workers and creating a more supportive climate are included.

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)0.028
metaresearch head score (Gemma)0.022
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 score0.116
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0300.013
Scholarly communication0.0050.003
Open science0.0020.008
Research integrity0.0020.004
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 head0.088
GPT teacher head0.404
Teacher spread0.315 · 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

Citations62
Published2003
Admission routes2
Has abstractyes

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