Situating platform gig economy in the formal subsumption of reproductive labor: Transnational migrant domestic workers and the continuum of exploitation and precarity
Bibliographic record
Abstract
In conversation with critical platform and labor studies, which tend to focus on drivers and food delivery workers, this article seeks to expand our understanding of the platform gig economy from the perspective of reproductive labor and migrant domestic workers. The exploitation of women’s unpaid and low-paid reproductive work has persisted throughout various stages of capitalist development. Migrant domestic workers’ underpaid reproductive labor becomes an essential site for primitive capital accumulation and the production of the labor force in the contemporary neoliberal global economy. Building upon analyses of the historical and contemporary circumstances of transnational migrant domestic workers in Canada, I argue that digital labor platforms become a technology-enabled, capital-driven force in the larger commodification and exploitation process of migrant workers’ reproductive labor, and such processes are underpinned by entangled structural and institutional forces of the uneven capitalist development, racism, patriarchy, and the state’s discriminatory (im)migration and labor policies. The article suggests that understanding the seeming prevalence of platform work should be situated in the continuous formal subsumption of reproductive labor and the class immobility of migrant domestic workers, and labor activism and movements should contest the entwined power dominations beyond merely demanding regulations over platforms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".