Decolonial ecofeminism: a paradigmatic contribution to critical research of gender, ecology and coloniality
Bibliographic record
Abstract
Systemic forces of power are deeply embedded in areas of ecological extraction. As such, it is imperative that theoretical stances employed to frame research of extraction centre intersections of power and the subsequent impacts for communities. To do so, this paper offers the convergence of ecofeminist and decolonial theory; a decolonial ecofeminism, as an complimentary paradigmatic framework to engage in critical research surrounding topics of gender, ecology and coloniality. Through a case study of a recent research project of gender and extraction in the Dominican Republic, this theoretical paper demonstrates the possibilities of a decolonial ecofeminism to situate women’s narratives of extraction within systems of power, illustrating the severity of gendered experiences caused and perpetuated by open-pit mining. This paper provides a thorough overview of decolonial and ecofeminist theories respectively, including key theorists, main tenets and significance for critical research. Further, the compatibility of these theories is revealed, establishing suitability for theoretical convergence to complement existing conceptual understandings. Through decolonial ecofeminism as a paradigmatic contribution, this work strives to build on existing debates surrounding coloniality and gender, exposing the exploitation of nature and women as neocolonial, capitalist violence, and enhancing opportunities for scholarly activism, disruption and resistance.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.107 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".