Identity formation, Christian networks, and the peripheries of Kachin ethnonational identity
Bibliographic record
Abstract
Abstract Why do regional identities develop (or not)? While we know about the institutional incentives that make some identities more salient than others, we know much less about the conditions that make nation‐builders more or less successful. To fill this gap, this paper examines the organizational dimensions of identity formation and the peripheries of Kachin nationalism in Myanmar. It argues that identity formation is shaped by political entrepreneurs’ capacity to (1) create inclusive inter‐elite alliances and (2) turn individuals into “citizens” of a larger ensemble. Empirically, it seeks to understand why we find resistance to a pan‐Kachin identity among two “Kachin” subgroups: Rawang and Lisu. The article shows that their conditional Kachin identity is the outcome of (1) incomplete inter‐elite alliances due to the uneven spread of Christian networks through which nation‐builders worked; and (2) the KIO’s variable and declining capacity to provide public goods inclusively across all Kachin groups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".