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Record W4285082607 · doi:10.1016/s2214-109x(22)00203-0

Work and health challenges of Indigenous people in Canada

2022· review· en· W4285082607 on OpenAlexafffundabout
Quentin Durand‐Moreau, Jesse Lafontaine, Jennifer Ward

Bibliographic record

VenueThe Lancet Global Health · 2022
Typereview
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Alberta
FundersFaculty of Medicine and Dentistry, University of AlbertaAlberta Medical AssociationUniversity of Alberta
KeywordsIndigenousRedressCommissionOccupational safety and healthMental healthSocioeconomic statusEnvironmental healthMedicineSocioeconomicsPolitical scienceEconomic growthGeographySociologyPopulationPsychiatryLaw

Abstract

fetched live from OpenAlex

The Truth and Reconciliation Commission of Canada has published 94 calls to action to redress the legacy of residential schools where thousands of Indigenous children have died. The objective of this narrative review is to address some of these calls by summarising the available evidence on work and health issues encountered by Indigenous workers in Canada. We searched seven databases to retrieve studies on Indigenous people, in Canada, and on occupational health as defined by the International Labour Organization. We included 31 studies, from which we found that Indigenous workers are experiencing intersectionality issues: in addition to having differential health issues related to a below-average socioeconomic status, Indigenous workers face discrimination in workplaces that affects their mental health. Indigenous workers might also cumulate occupational and environmental exposures from industries that have settled close to their dwellings (eg, exposure to polychlorobiphenyls). There is a scarcity of studies on major occupational health topics such as occupational cancers or musculoskeletal disorders in Indigenous people.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.909
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.236
GPT teacher head0.489
Teacher spread0.253 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations26
Published2022
Admission routes3
Has abstractyes

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