"We are the Living Dead": The Gendered Impacts of Open-Pit Mining in the Dominican Republic
Bibliographic record
Abstract
Despite a rhetorical commitment to enhancing community well-being, Canadian mining corporations have a history marked by ecological degradation and human rights violations, with women experience disproportionately negative impacts. While Latin America and the Caribbean (LAC) is a desired topography for open-pit mining, the geographical area of the Dominican Republic has been largely absent from the literature. As such, this dissertation, rooted in decolonial ecofeminism, enacted a critical narrative inquiry with 7 women from the Dominican Republic to explore the gendered impacts of open-pit mining on their health and well-being.\nThis thesis is composed of six chapters, with chapter one introducing the rationale, guiding research questions, key terminology and researcher reflexivity. Chapter two consists of a scoping review which synthesizes the peer-reviewed literature regarding the gendered impacts of mining in LAC, revealing gaps which initiated this research. Chapter three provides an in-depth discussion of the methods, methodologies, paradigmatic understandings and reflexive insights of the research process. Chapter four presents a thematic analysis which reveals the seven main themes that arose from the critical narrative inquiry. These themes include ecological destruction; physical health and well-being; emotional health and well-being; sociocultural erosion; deception and corruption; systemic forces of power; and resistance and repression. Chapter five consists of a critical analysis of the findings, illuminating significant contributions, discussing methodological insights and presenting the dissemination of research findings. The concluding chapter reveals the broader implications of the findings and future directions of research in the field of gender and mining.\nThrough a decolonial ecofeminist perspective, this dissertation situates women’s narratives within systemic forces of power and illustrates the severity of gendered experiences caused and perpetuated by open-pit mining projects. This work makes a new and important contribution to a growing body of literature regarding gender and extraction, disrupting dominant narratives of transnational extraction and promoting health and well-being for mining impacts communities.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".