Tensions in anti-colonial research: lessons learned by collaborating with a mining-affected indigenous community.
Bibliographic record
Abstract
Community-based nurse researchers strive to develop collaborative partnerships that are meaningful to the health priorities of participants and relevant to their sociopolitical realities. Within the context of global inequity, intersecting forces of privilege and oppression inevitably shape the research process, resulting in tensions, contradictions, and challenges that must be addressed. This article has 3 purposes: to examine the political context of mining corporations, to describe common health threats and challenges faced by mining-affected communities, and to reflect on research with a mining-affected Indigenous community in Guatemala whose health and capacity for self-advocacy are impacted by a legacy of colonialism. Using an anti-colonial lens, the authors discuss 3 central tensions: community agency and community victimhood, common ground and distinct identities, and commitment to outcomes and awareness of limitations. They conclude by offering methodological suggestions for nurse researchers whose work is grounded in anti-colonial perspectives.
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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 | 0.107 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.047 | 0.043 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.006 | 0.033 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".