Bibliographic record
Abstract
A notable exception to this failure to integrate skilled immigrant women workers into regulated professions is the feminized field of nursing.This chapter draws on fieldwork conducted with a government-funded pi lot proj ect (referred to here as "Nurture") to help foreign-trained nurses become licensed in Ontario, in order to examine a special case in which extensive reeducation was not required to reenter one's field in Canada.While locally, the high rate of reentry for nurses has been attributed to the success of this resettlement program, I assert that its prac ti tion ers can enter into Canadian venues because of the way nursing is understood as gendered labor. 1 After all, nursing is a feminized profession-that is, it is understood as " women's work"-and so workplace ideologies surrounding masculinized per for mances of a global modern worker are not applicable.The logics imposed in these classrooms, and the pedagogies employed, are rife with racial and gendered ideologies of appropriate citizenship and appropriate womanhood in a model of care.During classes at Nurture, a group of foreign-trained nurses and I learned how to control our affect for legibility on the job market, including how to manage conflict.The instructor, Libby, a Black Canadian nurse, had been working with the program as part of her ser vice to the professional nursing association.Conflict, she explained, could consist of "disagreement, crisis, clash, fight, or an argument" that could manifest both internally (guilt, anger, frustration) and externally (yelling at a colleague).In handling "one's own anger management, " the first strategy she offered was to "stop being
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 teacher head, 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".