Indigenous voices in the global public sphere: Analysis of approaches to journalism within the WITBN network
Bibliographic record
Abstract
Abstract The World Indigenous Television Broadcasting Network (WITBN) consists of Indigenous broadcasters from around the world. During the WITBN Conference WITBC 2012 in Guovdageaidnu, Sámiland (Norway), a number of interviews were conducted with Indigenous media workers from within the broadcast network. Based upon a selection of these interviews, this article aims to present an analysis of approaches to Indigenous (television) journalism drawing upon data from Australia, Canada, Finland, Hawaii, Norway, Scotland, Sweden, Taiwan and Wales. This analysis will be framed in relation to the wider context of Indigenous peoples’ rights and politics. Drawing upon theoretical frameworks on racism and exclusion vs democracy and inclusion based on self-determination, this article aims to highlight the role of Indigenous media and journalism in making the public sphere more diverse and creating new global networks between previously silenced voices with the help of new technical solutions. The article will demonstrate how, while presenting an Indigenous perspective of the world, these Indigenous broadcasters do ‘real journalism’ just as any majority broadcasting company and while perceiving their own Indigenous communities as their core audience, they aim to reach wider audiences with their programming, thus providing a window for majority audiences into Indigenous realities. The article also highlights how the international movement of indigeneity as a political process impacts upon Indigenous broadcasters in ways that are different from their autochthonous professional colleagues.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.016 | 0.033 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".