Violence as non-communication : the news differential of Kashmir and Northeast conflicts in the Indian national press
Bibliographic record
Abstract
This thesis seeks to explain the contradiction of ethno-national conflicts in northeast India involving much terrorism and violence not resonating in the New Delhi-based national press. Evidence suggests that the media cover only a third of ongoing global terrorist conflicts even though terrorism and violence have long been privileged in communications research as being irresistibly newsworthy. The case study is located in India, but selectivity is a global phenomenon with only few conflicts receiving sustained media attention: Northern Ireland, Basque separatism, Quebec, Kashmir, Catalonia, or the Middle East the rest are symbolically annihilated. I propose that the sustained coverage of a conflict in the national or international contexts depends on the key variable of the socio-cultural environment in which journalists operate. A conflict is likely to figure regularly in media content only if journalists see it as affecting or involving what they socially and culturally perceive to be the 'we' a similar conflict involving the socio-cultural 'they' may be routinely ignored or extended ad hoc coverage, even if it involves much violence and terrorism. The 'we'-'they' binary, used here as a socio-cultural concept, also connects with political debates about multiculturalism, recognition, citizenship and Orientalism. Located in the discourse of production of news, this study establishes that terrorism and violence as part of a conflict may not guarantee news coverage. Kashmir and northeast conflicts demonstrate several commonalities, but only the Kashmir conflict is routinely selected for sustained and prominent coverage. By mainly interviewing journalists, it is established that the northeast is routinely seen to involve and affect the socio-cultural 'they' hence its systemised low status in the news discourse compared with Kashmir, which is perceived to be located at the core of the 'we'. This news differential also suggests the existence of 'sub-Orients' within the Orient, even Orientalism within the Orient.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".