Bibliographic record
Abstract
There has been a wealth of research in Latin America on the most recent global intensification of extractivism, or the capitalist exploitation of natural resources. Some of this research has examined the resistance among front-line Indigenous and rural communities, and allied environmental groups, who are challenging the development of mega-scale mining, oil, gas, monoagricultural, and related infrastructural projects. Researchers have noted many similar tactical repertoires that can take multiple forms (through direct action, media representation, and in legal, political, and educational forums) and extend across geographic scales (local, national, regional, and transnational). Communications is key to much of their work; however there has been far less research examining the communications practices in any detail. This article focuses on the communications practices in use in three Indigenous led campaigns against extractivist projects in North America, the decade-old Unist’ot’en Camp in northwestern Canada, Idle No More, and the #NoDAPL of the Standing Rock Sioux. My findings indicate that a resurgent Indigenous movement, in concert with environmental and other settler allies, has adopted an array of communications practices that combine protective action on behalf of their lands and waters with the creation of new communities in place-based assemblies and social media and digital networks.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".