Migration and Labour Mobility:\nThe Narratives of Immigrant Women\nin Toronto, 1970s–1990s
Bibliographic record
Abstract
Oral histories can amplify the voices of marginalized, racialized women who have been otherwise excluded from history. The stories of six Caribbean women of colour who migrated to Canada between the 1970s and the 1990s lay bare the opportunities and the challenges of international labour mobility and migration. Shaped by the intersectionality of race, class, gender, and citizenship, the women were able to adjust to the demographic, social, political, and economic changes of the late twentieth century’s global economy by harnessing labour mobility. These women—and their life stories—form a salient part of the social history of immigration, domestic service, and health care in late twentieth century Toronto. Abstract: Les récits oraux permettent d’amplifier les voix des femmes marginalisées et racialisées qui ont autrement été exclues de l’histoire. Les témoignages de six femmes de couleur originaires des Caraïbes, ayant émigré au Canada entre les années 1970 et 1990, révèlent les débouchés et les enjeux de la migration et de la mobilité internationales de la main-d’œuvre. Façonnées par l’intersectionnalité de la race, de la classe, du genre et de la citoyenneté, ces femmes ont réussi à s’adapter aux changements démographiques, sociaux, politiques et économiques liés à la mondialisation de l’économie à la fin du XXe siècle, en tirant parti de leur mobilité de travail. Ces femmes — et leurs récits de vie — font partie intégrante de l’histoire sociale de l’immigration, du service domestique et des soins de santé dans le Toronto de la fin du XXe siècle.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.029 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".