Modern Communications Technology in Ethnic Nationalist Hands: The Case of the Kurds
Bibliographic record
Abstract
This article examines the effect of modern media and communications technology on ethnic nationalist resurgence, using the Kurds as a case example. Television, satellite communications, the Internet and easy access to publishing technology now facilitate ethnic nationalist challenges to state hegemony and monopoly of information. Additionally, modern media and communications technology can turn a humiliating defeat into a catalyst for a more unified, stronger, ethnic nationalist movement. Globally broadcast images of such a defeat arouse the passions and indignation of even those people who only nominally identify themselves with the ethnic group in question. At the same time, communications technology such as telephones, faxes and e-mail facilitate the channeling of such indignation into immediate group protest and action which, in turn, strengthens the ethnic identification of action participants.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.021 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".