Peaceful Returns: Reversing Ethnic Cleansing after the Bosnian War
Bibliographic record
Abstract
Abstract This article questions the conventional wisdom which claims forced migration is irreversible following massive ethnic cleansing campaigns, by investigating durable returns to pre‐conflict home communities in Bosnia‐Herzegovina. We formulate a set of novel hypotheses on the demographic determinants of return as well as on the role of social capital, nationalist ideology, integration, and war victimization. We use a 2013 Bosnian representative sample with 1,007 respondents to test our hypotheses. The findings support the expectation that gender and age have a major impact on return. Net of other factors, women and those experiencing wartime victimization are less likely to return. Older Bosnians with positive memories of pre‐conflict interethnic relations are more likely to return than younger persons or those with negative memories. Finally, ethnic Bosniacs are more likely to return than ethnic Croats or Serbs. More nationalistic internally displaced persons (IDPs) are less likely to return.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".