An Intersectional Approach to Family Life: Reflections on Same-Sex Marriage, Familisation Risks, and Defamilisation Risks in Mainland China
Bibliographic record
Abstract
This article focuses on how the policy on same-sex marriage and a person’s social locations impact upon Chinese lesbians’ life chances and welfare. Bringing the familisation and defamilisation literature, which has predominantly focused on heterosexual populations and families, into dialogue with an intersectionality perspective, we map the ways in which gender, sexuality, and class intersect in shaping lesbians’ experiences of defamilisation and familisation risks. The findings, drawn from interviews conducted in Beijing, China, reveal that the absence of legalised same-sex marriage, coupled with a lack of familial and societal recognition of same-sex relationships, exposes lesbians to both defamilisation and familisation risks, leading to difficulties in choosing whether and how to participate in the family. The intersectionality lens guides us to move beyond the heterosexual/homosexual boundary and to rethink the possibility of welfare alliances that can improve the welfare of not only lesbians but also other groups of women and minorities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".