Coping with further absences: Maaveerar Naal ceremonies in the postwar age
Bibliographic record
Abstract
Every year since 1989, LTTE supporters have commemorated the dead Tigers, called Maaveerar (“Great Heroes” in Tamil), in public ceremonies held all over the world. Among LTTE celebrations, Maaveerar Naal (lit. “Great Heroes’ Day”) is the most important because all the fighters are honoured collectively. The combatants are presented as having offered their life for Tamil Eelam. In this paper I will examine how the Maaveerar Naal ceremonies organised among the Diaspora have been affected by the defeat of the Tigers in May 2009. In particular I will focus on the strategies elaborated by LTTE supporters to cope with the numerous absences that the military rout involved. My analysis of the post-war period concerns the ceremony held last year in Novellara, a small town close to Reggio Emilia in northern Italy, where Tamil people coming from the centre and the north of Italy converged. The main data regarding the previous ceremonies are the result of the fieldwork among the Tamil Diaspora carried out in Italy from 2000 to 2008 and of participation in Maaveerar Naal celebrations in Montreal and in Paris.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".