Taking a learning approach to community-based strategic environmental assessment: results from a Costa Rican case study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper describes an innovative approach to environmental assessment that built local capacity enabling a more sustainable management of natural resources. It presents learning outcomes from a community-based strategic environmental assessment (CBSEA) involving communities from two Costa Rican watersheds who assessed the Instituto Costarricense de Electricidad's (ICE) proposed agro-conservation programme. Participants were engaged throughout the CBSEA process, from planning to the implementation of four highly interactive workshops representing steps in a strategic environmental assessment. Instrumental learning results included: learning about CBSEA and its role in programme planning; developing problem-solving skills related to assessing impacts and creating mitigation strategies; effective group-working strategies; and technical information. Communicative learning outcomes included becoming more self-aware, and appreciating environmental conservation and collaboration. ICE learnt a participatory methodology and reconsidered communities' role in programme planning. Findings contribute to understanding the process of adult learning in cross-cultural contexts and the link between individual learning and social action.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it