Gold mining in Guatemala: community health and resistance amidst violence
Bibliographic record
Abstract
Background: The Canadian mining industry has been linked to reports of environmental degradation, social insecurity and human rights violations. Due to a historical context of colonialism, genocide and state neglect, Indigenous populations may be particularly vulnerable to large-scale mining health threats.\nResearch Purpose: The overarching purpose of this investigation was to understand the influence of mining operations on the wellbeing of a Mam Mayan community in the Western highlands of Guatemala. Specifically, this study examined: (1) the political context in which mining operations are situated; (2) community mental health experiences; and (3) the role of resistance in shaping these political and health contexts. Methodology: Indigenous knowledges and a critical paradigmatic lens informed the research design, an anti-colonial narrative analysis, employing participatory action research (PAR) principles. Data collection was determined in collaboration with participants and included focus group interviews, photo-voice and one-on-one interviews. A total of 54 men and women from 14 villages in the municipality participated in the research.\nFindings: Macro-level findings revealed that community health challenges were embedded in intersecting, socio-politically complex landscapes. These conditions largely informed how local residents experienced the socio-cultural and economic changes occasioned by local mining operations. At the meso-level, community health experiences were reflected in an overarching narrative of social unraveling, characterized by a climate of fear and discord, and; embodied expressions of distress. In response to these threats, community acts of resistance revealed unique health strengths enacted through: a shared cultural identity; spiritual knowing and being; defending our rights, defending our territory; and speaking truth to power. Discussion and Conclusion: Community health experiences were embedded in systemic and intersecting macro-level forces of oppression and inequity. At the meso-level, an overarching narrative of social unraveling revealed an intricate mesh of interconnected community health threats. Residents attributed increased militarization, conflict and violence to the presence of local mining operations. Embodied expressions of distress were described as complex, severe and debilitating conditions of suffering. These findings suggest important implications for nursing and health policy and scholarship. Keywords: Indigenous health; community health; Guatemala; mining; intersecting; social unraveling; violence; distress; embodied; conflict
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".