The Borders that Divide, the Borders that Unite: (Re)interpreting Garo Processes of Identification in India and Bangladesh
Bibliographic record
Abstract
The people known as Garos, from the Garo Hills and adjacent (lowland) areas in India and Bangladesh, have never constituted one unified and self-defined in-group, although British colonial rule indeed produced a feeble notion of an imagined Garo community. Hence, the international border of 1947 formalized certain distinctions between hill Garos and lowlanders that had existed much longer, and gave a further impetus to the articulations of ethnic identities in different spaces. In recent years, however, we do see different attempts by the Garos to establish linkages across the border. This paper examines these processes of disconnection, exemplified by and through the international border, of unification (within the nation-state), and of (re)connection (across the border). We also try to show how the different strategies of the Indian and Pakistani/Bangladeshi states, in dealing with the populations in their borderlands, have impacted local processes of self-identification and self-assertion in significantly different ways, but with similar outcomes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".