Gender, Motherhood, and Ethnicity: ‘Dialectical Social Imaginaries’ among South and Southeast Asian Women in Hong Kong
Bibliographic record
Abstract
This article examines the ways in which gender, motherhood, and ethnicity shape the lived experiences of South and Southeast Asian mothers in Hong Kong. Through in-depth interviews with 54 mothers, we examine, what we term, ‘dialectical social imaginaries’ to understand how these mothers imagine their social surroundings and navigate challenges in this multicultural city, where traditional and progressive gender expectations coexist alongside ethnic diversity and discrimination. ‘Dialectical social imaginaries’ capture how individuals envision living together and interacting with different cultures, highlighting the tensions between following established norms and striving for change. The findings identify three types of ‘dialectical social imaginaries’, which are dialectical in that they swing between conformance to gender norms and transformation, between silence and resistance, and between distancing and belonging. Analyzing the reproductive and creative dimensions of these social imaginaries reveals diverse and often opposing forces of gendered expectations and cultures, demonstrating how socio-cultural forces facilitate and/or restrict individuals’ experiences of migration. This study contributes new insights to gender and migration studies by providing an analysis of the dialectic between social reproduction and transformation, and that of self/other entanglements. It highlights the conceptual utility of ‘dialectical social imaginaries’ for future sociological understandings of gender, migration, and culture.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".