Place and transformative learning in climate change focused community science
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
Community science involves the co-creation of scientific pursuits, learning, and outcomes and is presented as a transformative practice for community engagement and environmental governance. Emphasizing critical reflection, this study adopts Mezirow’s conception of transformative learning to theorize the transformative capacity of community science. Findings from interviews with participants in a community science program reveal critical reflection, although instances acknowledging attitudes and beliefs without challenging personal assumptions were more common. Program elements most likely to prompt participants to identify beliefs, values, and assumptions include data collection and interaction in team dynamics, whereas data collection in a novel environment was most likely to prompt participants to challenge their beliefs, values, and assumptions. A review of 71 climate change focused programs further demonstrates the extent that program designs support transformative learning. Key features of the community science landscape like the broad inclusion of stated learning objectives offer a constructive starting point for deepening transformative capacity, while the dominance of contributory program designs stands as a likely roadblock. Overall, this study contributes by applying a developed field to theorize transformation in relation to community science and by highlighting where facilitators should focus program design efforts to better promote transformation toward environmental sustainability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 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