Be the mother, not the daughter: Immigrant Chinese women, postpartum care knowledge, and mothering autonomy
Bibliographic record
Abstract
Scholars have documented the transformation of modern motherhood, as mothering practices have been a target of medical knowledge that comes to define correct modes of conduct for women caring for their pregnant bodies, undergoing childbirth and childrearing. Such accounts usually set scientific knowledge and medical authority in opposition to women's autonomy. Drawing on the interviews with immigrant Chinese mothers in Canada, we offer a different account of knowledge and agency in new motherhood. These women's often-intense experiences of intergenerational care-giving associated with the practice of zuo yuezi reveal a more fluid relationship between medical authority and mothering agency. We find that the central tension during the postpartum experience lies in intergenerational and family relationships. In this context, new mothers draw on alternative sources of knowledge-and medical professionals are one such key source-to demonstrate within the family their competence to make care decisions for themselves and their babies. These women's use of medical knowledge to counter a familial and intergenerational authority complicates dominant accounts about medicalisation, demonstrating that women's relationship to medical knowledge and authority maybe be far more fluid and complex than a standard account of medicalisation and loss of women's agency would predict.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".