Protracted Displacement in Conflict Zones: Refugees and Internally Displaced People in Jammu and Kashmir
Bibliographic record
Abstract
This study concentrates on the Indian state of Jammu and Kashmir and on those displaced people who, for the past six and a half decades, have remained invisible against the high profile background of the conflict between India and Pakistan over the Kashmir region. Their difficult situation arises in large part from the identity-based politics of Kashmir Valley which has led to the failure of the state (both national and regional) fully to respond to their very significant conflict-induced displacement resettlement requirements. This essay will address two distinct types of displacement which occurred in 1947 in the wake of Partition and the tribal invasion of the Princely State: the one involving the West Pakistan Refugees (WPR) who moved from Pakistani towns adjacent to the State of Jammu and Kashmir and had not been citizens of the Princely State of Jammu and Kashmir; and the other involving the Pakistan Occupied Kashmir Displaced People (PoKDP), citizens of the State, who moved from the Pakistan-administered part of Kashmir to the Indian-administered Kashmir, mainly the Jammu region and surrounding areas. Both groups belonged predominantly to the Hindu community. While the former, the WPR, remain stateless with no citizenship rights in J&K, the latter, the PoKDP, are considered by the State as temporary migrants, and thus have received only temporary relief.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".