Facilitating Co-Production of Transdisciplinary Knowledge for Sustainability: Working with Canadian Biosphere Reserve Practitioners
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
Sustainability scientists argue that diverse knowledge holders should work together in social learning processes to co-produce knowledge in support of sustainability. Yet, how to co-produce such knowledge remains unexplored. A multi-year, national knowledge sharing partnership among Canadian biosphere reserve practitioners, academic researchers and policy advisors revealed that a skilled facilitator was necessary for successful knowledge co-production. We draw attention to the multiple barriers to learning and knowledge co-production, and to the skills required of the facilitator to address them. The facilitator helped draw together local and formalized western knowledge systems (weaving) and diffuse innovations across local sites (out-scaling) and between local sites and the broader program network (up-scaling). Our experience reveals that simply bringing parties together will not generate transformative change for sustainability. Rather, multi-lateral facilitators are needed to ensure deliberate and managed interventions and to institutionalize learning across a diverse collective.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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