The psychological effects of state socialization: IGO membership loss and respect for human rights
Bibliographic record
Abstract
We present an interdisciplinary theory that considers how loss of membership in international organizations affects states’ human rights practices. Drawing mostly from social psychology and international relations research, we argue that states are socialized into the international community through a process of social influence, whereby they are incentivized to comply with group norms by the promise (threat) of social rewards (punishments). Social influence occurs when states form social bonds through interactions with other states. When social bonds are severed, fewer opportunities for social influence occur due to lower information to both the remaining states and the state that lost those social bonds. Thus, we hypothesize that the loss of membership from IGOs reduces incentives to comply with group norms and adversely affects human rights practices at home. A combination of propensity score matching/regression and autoregressive distributed lag (ADL) models on a global cross-section across the years 1978–2012 supports the theory. Specifically, losing at least one IGO membership leads to a long-run drop in human rights respect of about one quarter to one half standard deviation.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".