Reflexivity, embodiment, and ethics of care in rangeland political ecology: reflections of three feminist researchers on the experience of transdisciplinary knowledge co-production
Bibliographic record
Abstract
Although there is a growing interest in transdisciplinary knowledge co-production approaches applied to rangeland political ecology, the research paradigms and methodologies still dominating this field of research leave little room for equitable engagement with research participants and genuine action-oriented research. In this article, we provide a reflection on new practices grounded in feminist studies of science and care ethic literature to orient transgressive and engaged transdisciplinary political rangeland ecology research. Feminist epistemologies call for reflection on who produces knowledge and how such knowledge is used and shared. Feminist practices, such as reflexivity, embodiment, reciprocity, and care, cultivate awareness of the power dynamics embedded in the research process and motivate researchers to counteract asymmetrical or extractive relationships when we identify them. We first introduce the scholarship that inspires key principles of our feminist research approach and then reflect on our experiences as researchers and as activists working with Spanish and Catalan networks of women pastoralists. Three research questions guide our reflective process: (i) how can feminist theories of knowledge co-production contribute to rangeland political ecology; (ii) how can feminist methodologies be applied in practice so that collaboration between women pastoralists, their organizations, and researchers is mutually reinforcing, care-full, and action-oriented; and (iii) what are the challenges and limitations of our experiences to foster transformation and emancipation in knowledge co-production processes?
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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 | 0.035 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.035 | 0.086 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.004 | 0.024 |
| Research integrity | 0.008 | 0.016 |
| 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".