Rerouting the Narrative: Mapping the Online Identity Politics of the Tamil and Palestinian Diaspora
Bibliographic record
Abstract
Drawing on the e-Diasporas Atlas project ( www.e-diasporas.fr ) and original empirical research, this study examines the complex role of the World Wide Web in supporting and enabling new types of diaspora identity politics. It compares the online identity politics of two conflict-generated diasporas: Tamils and Palestinians. Both of these stateless diaspora communities maintain a strong web presence and have mobilized around various secessionist attempts, grievance narratives, issue-agendas, and calls for the right to self-determination that have garnered significant attention from the international community and mainstream media in recent times. Analytical concepts from transnational advocacy networks (TANs) and social movement literature are used to draw attention to the dynamic identity-based processes and framing mechanisms that connect diasporic demands and political claims across online and offline environments. The data combine Tamil and Palestinian e-Diasporas hyperlink network maps with web-based content analysis and key respondent interviews. The study argues that online diasporic exchanges transcend host–homeland territorial boundaries and invite comparatively expressive forms of identity-based political engagements that are simultaneously both deeply local and digitally global. In particular, the analysis demonstrates that human rights–based language offers a unique streamlining bridge between various locales, countries of settlement, and the international system more broadly.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".