MétaCan
Menu
Back to cohort
Record W2411017345

Occupational Health of Newcomers and Immigrants to Canada

2013· article· en· W2411017345 on OpenAlexaboutno aff
Iffath Unissa Syed

Bibliographic record

VenueEurope PMC (PubMed Central) · 2013
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthImmigrationOccupational safety and healthEthnic groupPsychological interventionSocial determinants of healthPolitical scienceDemographic economicsMedicinePublic healthPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Previous discourses in occupational health and medicine suggest that newcomer and immigrant groups experience high rates of work-related illness and injuries, possibly resulting from working conditions, social exclusion, as well as participation in precarious work. Often, social circumstances lead to adverse health outcomes including mental, psycho-social, and physiological. This investigation's aim was to gather a rich understanding of the evidence for work-related illness, morbidity and mortality among immigrant and newcomer groups from urban areas such as Montreal, Toronto, and the Greater Toronto Area, locations which have been popular destinations for migrant settlement and labor market trends in the last two decades. This study focused on elements from the political economy, social determinants of health, and social justice lenses to examine the concept of the new visible minority labor diaspora in the Canadian context, evidence for occupational disease acquired in the workplace among these vulnerable groups, and how such illness intersects culture, employment background, and gender. Evidence of income disparities from the literature was compared to Statistics Canada 2006 census data and adjusted for inflation. This analysis confirmed the negative effects of resettlement stress and precarious working conditions experienced by ethnic and racial minorities. Work-related musculoskeletal conditions, workplace violence, mental health issues due to overt discrimination and profiling, as well as exposures to second hand-tobacco smoke have been described. In addition, large disparities in earnings were widely reported. The implications of these findings has led to suggested interventions to address these issues.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.001
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.321
Teacher spread0.281 · 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 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueEurope PMC (PubMed Central)Same topicEmployment and Welfare StudiesFrench-language works237,207