Multifaceted precarity: pandemic experiences of recent immigrant women in the accommodation and food services sector
Bibliographic record
Abstract
The COVID-19 pandemic disproportionately affected those who face historical and ongoing marginalization. In centering pandemic experience of recent immigrant women in the accommodation and food services sector in Canada, we examine how their precarious work translated to experiences of work precarity and wellbeing. This paper illuminates how pre-existing and ongoing marginalization are reproduced during a health crisis for those at the intersection of gender, race, migration, and labour inequities. Using semi-structured interviews and systematic analysis using the Work Precarity Framework, we found that the pandemic exacerbated pre-existing socio-economic marginalization and resulted in unique experiences of work precarity. The latter was experienced as precarity of work (unpredictable work hours and job or employment insecurity), precarity from work (inadequate incomes), and precarity at work (physical, psychological, and relational unsafety). Work precarity stood out as a social determinant of health in relation to its outcome of degraded mental health and wellbeing. Recognizing the role of policies in producing, reproducing, and distributing precarity, we recommend policy directions to reduce social inequities in pandemic recovery.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".