Harassment and Violence faced by Latinas on Ontario Construction Industry work sites
Bibliographic record
Abstract
The aim of my dissertation is to examine the Harassment and Violence (HV) that Latinas face while working in the Ontario Construction Industry (OCI). I was specifically interested in the toxic impact HV has on Latina worker’s professional careers, as well as their personal lives. My qualitative research interviews (pláticas) with fourteen Latina construction workers, provided me with the capacity to explain how the labour they perform, and the legal invisibility by which they are defined, systematically combine to disenfranchise Latinas. I explain how the hyper-visible identity of Latinas on job sites, compounds the invisibility of their labour, even as language barriers significantly diminish their individual capacity to report and combat HV effectively. This dissertation also illuminates the persistent state of vulnerability (harassment, wage theft, and/or working in dangerous conditions) experienced by Latinas working without status in the OCI. I open with a literature review illuminating my uniquely intersectional, methodological position as a Canadian-born, Spanish-speaking academic researcher with more than two decades of experience working as a safety inspector in the OCI. My pláticas with fourteen Latinas working in the OCI reveal how workplace dynamics and regulatory inconsistencies contribute to their vulnerability to supervisory exploitation and discrimination from co-workers. The concepts of tokenism, intersectionality, and the conditionality of precarious status help explain how systemic labour policies have placed women in positions where following workplace regulations can inadvertently reinforce their collective marginalization. I found that the toxic, racialized, gendered culture of the OCI is reproduced even when women receive status, such as in the case of supervisors. I recommend a systemic shift in the culture of the OCI which keeps HV underground and normalizes the approach to Latina women in the industry. My dissertation concludes by recommending that support groups, operating outside of state structures, should be funded to serve as the frontline of protection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".