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Record W2046154622 · doi:10.1353/ces.2014.0045

Claiming Rights to Workplace Safety: Latin American Immigrant Workers in Southwestern Ontario

2014· article· en· W2046154622 on OpenAlexvenueaboutno aff
Tanya Basok, Alan Hall, Eloy Rivas

Bibliographic record

VenueCanadian ethnic studies · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationCitizenshipLatin AmericansEthnic groupPolitical scienceSociologyGender studiesLawPolitics

Abstract

fetched live from OpenAlex

Drawing on the studies of citizenship practices and health and safety literature, this paper explores the reporting of workplace injuries and hazards among Latin American immigrants in Southwestern Ontario. The paper examines how (under-)reporting is shaped by three conditions: the knowledge of workers’ rights, job (in)security, and ethnic identities. Recognizing knowledge as a significant factor which enables or constrains the capacity to claim one’s citizenship rights, we demonstrate that even when Latin American immigrant workers develop a good understanding of their rights, many are still unable to assert them. We argue that this lack of rights access reflects the intersection of two relevant factors – workplace (in)security and ethnic and immigrant identities – which discourage their reporting. In particular, we demonstrate that since Latin American immigrants often find themselves in subordinate positions in the Canadian labour market, they choose not to report injuries and unsafe working environments for fear of discipline and reprisals. In addition, immigrant, regional, ethnic, and home country identities, all of which can limit or contradict a full sense of citizenship, appear to exert some influence on the way workers understand their workplace rights. The paper is based on 44 in-depth interviews conducted with Latin American immigrants in 2010. Cet article analyse les déclarations sur les dangers et les accidents dans le milieu du travail parmi les immigrants latino-américains du sud-ouest de l’Ontario, en s’appuyant sur les études des pratiques citoyennes et sur la bibliographie dans le domaine de la santé et la sécurité. L’article examine la manière dont ces déclarations sont influencées par trois facteurs : la connaissance des droits des travailleurs, la sécurité d’emploi et les identités ethniques. Bien que la connaissance soit un facteur significatif qui favorise ou empêche la capacité d’affirmer ses droits de citoyenneté, les auteurs démontrent que, même quand les travailleurs migrants d’origine latino-américaine développent une bonne compréhension de leurs droits, beaucoup d’entre eux ont de la difficulté à les exercer. Les auteurs expliquent que ce manque d’accès aux droits reflète l’intersection de deux facteurs importants – l’insécurité dans le lieu de travail et les identités ethniques et immigrantes – qui découragent leur exercice. En particulier, on démontre que, du fait que les immigrants latinoaméricains se trouvent souvent dans des positions subordonnée dans le marché du travail canadien, ils choisissent de ne pas déclarer les accidents et les conditions dangereuses des milieux professionnels en raison de la crainte des sanctions. Aussi, les identités immigrantes, régionales, ethniques ou du pays d’origine, toutes lesquelles peuvent limiter ou contredire un sens plein de la citoyenneté, semblent avoir une influence sur la façon dont les travailleurs comprennent leurs droits. L’article porte sur 44 entrevues en profondeur réalisées auprès d’immigrants latino-américains en 2010.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.005
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.170
GPT teacher head0.474
Teacher spread0.303 · 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 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

Citations17
Published2014
Admission routes2
Has abstractyes

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