One foreign force, two nationalisms: How Chinese nationalism resists external LGBT human rights pressure
Bibliographic record
Abstract
International pressure on human rights can mobilize domestic social and political change but can also be manipulated and resisted, which necessitates exploring the problems and mechanisms within human rights discourses. Focusing on Chinese LGBT issues and examining Chinese sexual nationalist discourses, this study investigates how Chinese nationalism is employed to resist international LGBT rights pressure. It reveals that, although external entities have pressured LGBT rights through naming, shaming, and even direct advocacy, these external pressures face two dilemmas rooted in the principles of particularism and noninterference. These dilemmas have become significant points of contention for the Chinese state and nationalists, who respond to external LGBT rights pressure by emphasizing discourses of authenticity and security. Specifically, Chinese nationalist discourse leverages the principle of particularism to emphasize its distinctive sexual traditions and values, while employing the principle of noninterference to manipulate external LGBT rights pressure as originating from hostile foreign forces. Notably, Chinese nationalism is not a monolithic ideology; instead, it encompasses two contrasting forms of sexual nationalism—namely, macho nationalism and homonationalism. Despite differences in defining authentic Chinese sexual traditions, both forms of nationalism converge in perceiving external LGBT support as foreign forces.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| 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".