Labor Migration and the Missing Work of Homemaking: Three Forms of Settling for Chinese-Canadian Migrants
Bibliographic record
Abstract
Much of migration theory has come to revolve around the category of the “labor migrant,” without taking into account labor, like homemaking, that remains unrecognized by the market. Drawing from qualitative interviews with thirty-one Chinese migrants in different stages of making a move from Beijing to Vancouver, we attempt to bring better visibility to how the labor involved in homemaking intersects with migration. Defining homemaking as work in the pragmatic-existentialist context of the stabilization of everyday routines, we uncover three themes to homemaking work: settling in, settling down, and settling for. Discussion of these themes reveals two important issues for migration theory: settlement relies upon the work of homemaking and the work of homemaking in many cases motivates migration. For these reasons, the work of homemaking should be more carefully studied within the migration literature.
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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 | 0.004 | 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 | 0.044 | 0.031 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| 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".