Identities-at-Intersections: The Case of Racialized Female Migrant Teachers in Canada
Bibliographic record
Abstract
This research focuses on the unemployment and underemployment of racialized female migrant teachers in Canada, particularly in Ontario. It investigates how the social categories of the identities of female migrant teachers affect their access to the labour force. Identity is conceptualized as produced by the meanings of difference placed upon these social categories, through the power relations one navigates. The research asks: how have the identities of racialized female migrant teachers in Canada, as embedded within the social categories of race and ethnicity, sex and gender, economic class and political status, language/s spoken and linguistic accents, affected their access to the Canadian teaching workforce? The main argument is that the racialized female migrant teachers’ identities are identities-at-intersections. These identities greatly affect their access to the teaching workforce, place them in politically challenging positions, and are produced by and through their navigation within the intersections. Intersections are the created, perceived, visible, and invisible links between and among the social categories that form an identity. The social spaces within the intersections affect the positioning of minoritized subjects, such as racialized female migrant teachers, within education as a polity and other structures of hegemony. Narratives of 17 female migrant teachers, registered with the Ontario College of Teachers, from the Greater Toronto Area (GTA), Ontario, are utilized as standpoint epistemologies to support the main argument. In examining how racialized female migrant teachers face barriers in their access to the teaching workforce and political contexts, the conceptual analysis draws on the concept of identities-at-intersections to consider: (1) the global process of feminization of migration instigates social reproduction mechanisms and inequality; (2) the practices of racialization in societal structures, in education as a polity, in the labour market, and within Canadian nation-building, further complicate the exercise of employment and citizenship rights of minority groups, such as racialized immigrant women; (3) the persistence of neo-colonial and capitalist practices results in the continuous segregation and racialization of immigrant women; (4) despite the structural forces that work against racialized female migrant teachers as identities-at-intersections, their lived experiences manifest the use of agency and forms of resistance.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.096 | 0.019 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| 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".