Network discrimination against LGBTQ minorities in Taiwan after same-sex marriage legalization: a Goffmanian micro-sociological approach
Bibliographic record
Abstract
In 2019, the government of Taiwan legalized same-sex marriage, the first to do so in Asia. Yet, despite its celebration as a sign of liberal progress, legalization appears at odds with the results of referendums that show a majority of Taiwan citizens oppose LGBTQ acceptance, following a steady decline in tolerance for LGBTQ people in Taiwan. To explain this, this article adopts a Goffmanian micro-sociological approach to interrogate LGBTQ experiences of stigma and discrimination in their networks. Using narrative and go-along interviews with LGBTQ people in Kaohsiung, Taiwan in 2019, this article shows (1) latent forms of discrimination in families and at workplaces, (2) the intensification of discriminatory scrutiny within these spaces in the wake of legalization, (3) mental health consequences, and (4) social enclaves that offer some reprieve from discriminatory pressures. This article identifies a need for greater resource allocation to create safe spaces for members of the LGBTQ community and anti-discrimination policies to combat the capillary forms of discrimination that have arisen after same-sex marriage legalization.
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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 | 0.001 | 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 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".