Bibliographic record
Abstract
Valerie Alia’s book, The New Media Nation: Indigenous Peoples and Global Communication (New York: Berghahn Books, 2012, 270 pp.), points the way to major communication breakthroughs for traditional communities around the world, in turn fostering a more democratic media discourse. From Canada to Japan, and Australia to Mexico, this ambitious and wide-reaching work examines a broad international movement that at once protects ancient languages and customs but also communicates to audiences across countries, oceans, and political boundaries. The publication is divided roughly into five sections: The emergence of a global vision for Indigenous communities scattered around the world; government policy obstacles and opportunities; lessons from Canada, where Indigenous media efforts have been particularly dynamic; the global surge in television, radio and other technological media advances; and finally the long-term prospects and aspirations for Indigenous media. By laying out such a comprehensive groundwork for the rise of global Indigenous media over a variety of formats, particularly over the past century, Alia shows how recent social media breakthroughs such as the highly successful #IdleNoMore movement—a sustained online protest by Canada’s First Nations peoples—have been in fact inevitable. The world’s Indigenous communities have leveraged media technologies to overcome geographic isolation, to foster new linkages with Indigenous populations globally, and ultimately to mitigate structural power imbalances exacerbated by non-Indigenous media and other institutions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.029 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".