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Record W6921780176 · doi:10.7916/dp92-wy74

A Scoping Literature Review of Work-Related Musculoskeletal Disorders Among South Asian Immigrant Women in Canada

2025· article· en· W6921780176 on OpenAlexaboutno aff

Bibliographic record

VenueColumbia Academic Commons (Columbia University) · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationSouth asiaEthnic groupEpidemiologyPopulationMEDLINE

Abstract

fetched live from OpenAlex

Global migration has recently garnered intense interest from a public health standpoint. Topics concerning migration, such as push-pull theories, resettlement stress, the healthy immigrant effect, cultural assimilation, and occupational health issues, are increasingly being studied. The occupational health of migrant workers — particularly female workers — is an especially important area for research. Migrant women have an increased vulnerability to occupational musculoskeletal disorders (MSDs) in low-paid and gendered occupations such as those in the textile, hairdressing, cleaning and garment-work industries, accompanied by mental stress due to production demands. One of the fastest growing communities in Canada is that of female migrants from South Asian (SA) countries, comprised of Pakistan, Bangladesh, Sri Lanka, India and Nepal.

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)0.009
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.076
Threshold uncertainty score0.344

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0260.046
Science and technology studies0.0050.003
Scholarly communication0.0080.002
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.004
GPT teacher head0.214
Teacher spread0.210 · 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 designSystematic review
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

Citations0
Published2025
Admission routes1
Has abstractno

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