Bodies, Shrines, and Roads: violence, (im)mobility and displacement in Sri Lanka
Bibliographic record
Abstract
In Sri Lanka, gender and national identities intersect to shape people's mobility and security in the context of conflict. This article aims to illustrate the gendered processes of identity construction in the context of competing militarised nationalisms. We contend that a feminist approach is crucial, and that gender analysis alone is insufficient. Gender cannot be considered analytically independent from nationalism or ethno‐national identities because competing Tamil and Sinhala nationalist discourses produce particular gender identities and relations. Fraught and cross‐cutting relations of gender, nation, class and location shape people's movement, safety and potential for displacement. In the conflict‐ridden areas of Sri Lanka's North and East during 1999–2000, we set out to examine relations of gender and nation within the context of conflict. Our specific aim in this article is to analyse the ways in which certain identities are performed, on one hand, and subverted through premeditated performances of national identity on the other hand. We examine these processes at three sites—shrines, roads and people's bodies. Each is a strategic site of security/insecurity, depending on one's gender and ethno‐national identity, as well as geographical location.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".