Integrating Multiple Knowledge Systems into Environmental Decision-making: Two Case Studies of Participatory Biodiversity Initiatives in Canada and their Implications for Conceptions of Education and Public Involvement
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
Biodiversity initiatives have traditionally operated within a ‘science-first’ model of environmental decision-making. The model assumes a hierarchical relationship in which scientific knowledge is elevated above other knowledge systems. Consequently, other types of knowledge held by the public, such as traditional or lay knowledges, are undervalued and under-represented in biodiversity projects. Drawing upon two case studies of biodiversity initiatives in Canada, this paper looks at the role that constructivist conceptions of education play in the integration of alternative knowledge systems in environmental decision-making. In so doing, it argues that the conservation, sustainable use and equitable sharing goals outlined by the Convention on Biological Diversity (signed in 1992 under the auspices of the United Nations Environmental Programme) demand new models of governance which embrace the adaptive management qualities of learning organisations.
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 | 0.000 | 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 | 0.000 | 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