Can Transnational Norm Advocacy Undermine Internalization? Explaining Immunization Against LGBT Rights in Uganda
Bibliographic record
Abstract
Norm cascades often spark resistance from states under pressure to conform. Some react by further distancing themselves from the norm—a process known as “norm backlash.” We identify a particular kind of norm backlash: the creation of legal barriers aimed at fending off a transnationally diffusing norm by blocking the ability of local actors to advocate for it. We call this phenomenon “norm immunization” and provide an account of the conditions that bring it about. In this account, transnational advocacy increases the local salience of the norm, which is discursively constructed as a national threat that calls for defensive regulations against the advocacy of the threatening norm. Using this model, we analyze Uganda’s immunization against LGBT rights as instantiated in the Anti-Homosexuality Act of 2014. We find that the successful efforts of LGBT rights advocates elsewhere indeed precipitated the discursive construction of those rights as a national threat in Uganda, thereby unintentionally contributing to the adoption of the norm-immunizing law.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".