Nationalism and Media Coverage of Indigenous People's Collective Action in Canada
Bibliographic record
Abstract
Indigenous peoples in Canada have engaged in hundreds of collective action events. The media are the key means through which the general public learns about these actions. However, the media do not simply mirror events. Instead, coverage tends to emphasize certain aspects of indigenous peoples’ collective action events while overlooking others. While early research emphasized the tendency of the mainstream media to portray these events as violent and militant, more recent scholarship has focused on nationalism and the ways that coverage of these actions creates an “us” vs. “them” binary. In this paper we build on this latter work by identifying the specific characteristics associated with each side of this binary. We analyze several hundred Canadian newspaper articles about a key set of events that took place during the 1990s. We find that the media repeatedly draws on frames that portray Indigenous peoples’ protest as criminal, divisive, and expensive. These assessments are made in implicit contrast with non-Indigenous people, or “good” citizens, as law-abiding, peaceful, and tax paying. Media stories therefore frame Indigenous challengers in a way that make them appear to be less deserving citizens of the nation.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".