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Record W2026958096 · doi:10.2190/hs.38.1.a

Broken English, Broken Bones? Mechanisms Linking Language Proficiency and Occupational Health in a Montreal Garment Factory

2007· article· en· W2026958096 on OpenAlexaffabout
Stéphanie Premji, Karen Messing, Katherine Lippel

Bibliographic record

VenueInternational Journal of Health Services · 2007
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsAffect (linguistics)InterpreterImmigrationOccupational safety and healthEthnic groupFactory (object-oriented programming)Work (physics)Language barrierPublic relationsPsychologySociologyMedicinePolitical scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

Language barriers are often cited as a factor contributing to ethnic inequalities in occupational health; however, little information is available about the mechanisms at play. The authors describe the multiple ways in which language influences occupational health in a large garment factory employing many immigrants in Montreal. Between 2004 and 2006, individual, semi-structured interviews were conducted with 15 women and 10 men from 14 countries of birth. Interviews were conducted in French and English, Canada's official languages, as well as in non-official languages with the help of colleague-interpreters. Observation within the workplace was also carried out at various times during the project. The authors describe how proficiency in the official languages influences occupational health by affecting workers' ability to understand and communicate information, and supporting relationships that can affect work-related health. They also describe workers' strategies to address communication barriers and discuss the implications of these strategies from an occupational health standpoint. Along with the longer-term objectives of integrating immigrants into the linguistic majority and addressing structural conditions that can affect health, policies and practices need to be put in place to protect the health and well-being of those who face language barriers in the short term.

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)0.007
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.435
Teacher spread0.407 · 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 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

Citations82
Published2007
Admission routes2
Has abstractyes

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