#Resistencia: Indigenous Movements, Social Media, and Mobilization in Latin America
Bibliographic record
Abstract
Abstract Indigenous peoples in Latin America have produced some of the region’s strongest and most enduring social movements, drawing on a diverse repertoire of contention to pursue their goals. In the twenty-first century, social media have transformed the landscape of collective action, compelling Indigenous movements to navigate the evolving dynamics of digital platforms. There is an ongoing debate in the literature regarding the role of social media in mobilization. But we know relatively little about how social media fit into the tactical repertoires of Indigenous actors and what tasks these platforms are used for. This article addresses this gap through an examination of how Indigenous actors use social media during protest events. We conducted a comparative analysis of social media content produced by Indigenous social movement organizations during major protest events in three countries from 2018 to 2019. We find that the most common functions include activating supporters and exposing state violence. These functions support several of the organizations’ core mobilization tasks by providing actors with tools to complement collection action.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".