Framing Indigenous protest in the online public sphere: A comparative frame analysis
Bibliographic record
Abstract
Indigenous social movement organizations are increasingly using social media to engage in strategic framing, a dynamic discursive process that seeks to attribute meaning to events and circumstances. But there remains a gap in our knowledge with respect to the impact of social media on the capacity of Indigenous actors to engage in frame competition in the virtual world. Based on a comparative frame analysis of online content in three Latin American countries where Indigenous organizations have recently engaged in large-scale protest, we ask to what extent the frames generated by Indigenous actors on social media are reflected in the online public sphere. We examine how their protest action is framed by Indigenous organizations themselves, the media, and government agencies. We find that social media do provide an outlet for Indigenous actors to disseminate counter-hegemonic frames. But state and media actors do not engage with Indigenous frames disseminated over social media, and their messages do not change the tone or direction of online discourse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".