Competing for Victim Status: Northern Muslims and the Ironies of Sri Lanka’s Post-war Transition
Bibliographic record
Abstract
The northern Muslims together with all protracted IDPs displaced prior to 2008 became a low priority caseload for return and resettlement assistance in the aftermath of the ‘end’ of the war in Sri Lanka in 2009. Framed in terms of an ethics of ‘greatest need’ connected only to funding availability, all old IDPs lost out in the resettlement process. This paper attempts to decentre this idea of economic limits and humanitarian need by discussing the manner in which such ideas of ‘greatest need’ actually emerge from discourses about victimhood that are part of an ethical humanitarian project to which local politics are irrelevant. This paper will show, however, that these initiatives consistently intersect with local power hierarchies and local ideas of legitimacy and belonging. Therefore, this paper will look at the manner in which the war related victim discourse of international humanitarianism, helped to exacerbate northern Muslim’s own marginality and continued exclusion from the north. This paper will also look at the manner in which victimhood narratives are mobilized in Sri Lanka by electoral politics and displaced IDP activists themselves, and will speculate about the efficacy of the victim identity for political and social transformation during this time of transition in Sri Lanka.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".