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Record W4289527223 · doi:10.3233/wor-210895

Workers’ compensation experience in some Indigenous Northern Ontario communities

2022· article· en· W4289527223 on OpenAlexaffabout
Nancy Lightfoot, Darrel Manitowabi, Victoria H Arrandale, Nathaniel Barnett, Carmen Wabegijig-Nootchtai, Mary Lynn Odjig, Jeff Moulton, Julie Fongemy, Michel Larivière, Zsuzsanna Kerekes, Linn D. Holness, Leigh MacEwan, Tammy Eger, Wayne Warry

Bibliographic record

VenueWork · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsOntario Ministry of LabourNOSM UniversityAssembly of First NationsUniversity of TorontoLaurentian University
Fundersnot available
KeywordsIndigenousFocus groupThematic analysisCompetence (human resources)Compensation (psychology)Financial compensationBusinessQualitative researchWorkers' compensationParticipatory action researchPublic relationsNursingPsychologyMedical educationMedicinePolitical scienceSociologySocial psychologyMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: There is a dearth of research about occupational health and safety experience in Indigenous communities and compensation applications from Indigenous workers appear limited. OBJECTIVE: This qualitative descriptive study was designed to explore workers' compensation experiences in some Canadian Indigenous communities. METHODS: A community-based participatory research approach was used to conduct focus groups (n = 25 participants) in three Northeastern Ontario (NEO) Indigenous communities and at one NEO Indigenous employment centre. Semi-structured focus group questions addressed community experience with workers' compensation, the compensation process, and discussion of a training session about the process. Reflexive thematic analysis followed Braun and Clarke procedures. RESULTS: Discussion with study participants resulted in these themes: 1) both lack of knowledge, and knowledge, about compensation demonstrated, 2) impact of lack of compensation coverage and need for universal coverage on reserve, 3) need for community training sessions about workers' compensation, 4) workload and financial impact of workers' compensation on reserve, and 5) requirement for cultural competence training in the compensation board. CONCLUSIONS: This qualitative descriptive study revealed the: need for more information about applying for workers' compensation and navigating the process, need for universal workplace insurance coverage in Indigenous communities, demand for community-based compensation process training, community costs of compensation, and the requirement for cultural safety and competence training for compensation organization employees. More education about the workers' compensation process would be of benefit to leadership, health care providers, administrative personnel, employers, and employees on reserves. Nurses in community health centres are well situated to provide further guidance.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.997

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 studies0.0100.000
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 head0.035
GPT teacher head0.293
Teacher spread0.258 · 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 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

Citations0
Published2022
Admission routes2
Has abstractyes

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