Sacred Sites Protection and Indigenous Women’s Activism: Empowering Grassroots Social Movements to Influence Public Policy. A Look into the “Women of Standing Rock” and “Idle No More” Indigenous Movements
Bibliographic record
Abstract
Religion and public policy are interconnected across a variety of issues. One aspect where this linkage has been understudied is religion and Indigenous sacred sites protection. This article aims to address this gap by analyzing how Indigenous women’s activism advances this cause. The focus is on how Indigenous Peoples, specifically women, use grassroots activism to provoke change on public policy in the context of the protection of Indigenous sacred sites. Two case studies are used to illustrate this concept: the American “Women of Standing Rock” and the Canadian “Idle No More” grassroots social movements. My analysis draws from interpretative methods. Interpretative research revolves around the concept of individuals as active producers of meaning. The women-led grassroots social movements at issue highlight a fundamental lack of awareness of the historical and current struggles of Indigenous Peoples, both in the US and Canada. Modern technologies and social media provide democratic means for grassroots social movements to be heard and empowered. The growing movement by Indigenous women to assert their rights, and their quest for self-determination in land use and sacred sites protection create a positive discourse that advances Indigenous women’s position in crossing the obstacles onto “institutional places of privilege,” hence influencing public policy.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.036 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| 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".