Strengthening collaborative capacity: experiences from a short, intensive field course on ecosystems, health and society
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
A key capacity for engagement in the emerging field of ecohealth is the ability to work collaboratively. Between 2008 and 2010, the Canadian Community of Practice in Ecosystem Approaches to Health collectively designed and delivered three foundational, intensive, field courses. This paper presents findings derived from both quantitative and qualitative student course evaluation survey data. New insights arise around: the diverse opportunities for learning collaboratively in order to tackle complex socio-ecological issues, the social dynamics of collaborative relationships and learning, and the learning challenges that arise during intensive field courses. The lessons learned from these foundational years have enhanced understanding of the interrelated contributions to collaborative learning and relationship building and their relevance to addressing issues spanning ecosystems, health and society.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it