Community-Based Action Research Approaches, Environmental Conservation, Economic Development, and Ethical Tensions: Reflections on Work in Peru and India
Bibliographic record
Abstract
Community-based action research (CBAR) is designed to facilitate community members’ identification of challenges in their lives, as well as to collaboratively develop ways to confront those challenges. It is also designed to be an inherently ethical and justice-oriented paradigm for social change and inquiry. When working with community members in areas such as the Peruvian Andes and North India, the problems community members now identify inevitably include the effects of environmental degradation and climate change on the community, as well as challenges with economic opportunities. When engaging in collaborative action to address these challenges, tensions can arise regarding community land-usage and its economic implications. Inherently, there are ethical implications when tensions arise between different facets of community identified needs and the possible effects of solutions. In this paper, we reflect on two projects that have had ethical tensions and consider ways CBAR can transform tensions into constructive ways forward.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.011 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".