Leadership in partnership research in the context of sustainable development.
Bibliographic record
Abstract
Climate change resilience (CC) calls for actions to build and improve resilience that needs to be integrated into a holistic thinking and strategic planning process to give these actions the importance they deserve. In this context, we have the right to ask ourselves: who can take initiatives to launch these processes? Who is in a position to take the lead in launching more targeted actions? Leadership is not confined to people who are at the top of a hierarchy, ex. the mayor, the elected representatives, ... Such processes have been initiated in many jurisdictions across Canada by actors not associated with local or regional governments. In the context of sustainable development, leadership requires "leaders" to recognize the need to empower other actors, including citizens, to assume the leadership of other actions and processes within a particular strategic orientation – reinforce resilience to CC. This reasoning is based on the principles of sustainable development which requires recognition of the contribution of each actor / group of actors and an understanding of the interests of each person involved. It is important to empower as many people as possible and not to focus on elected officials and professional staff – hence the construction of decentralized leadership and, ultimately, new governance.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.042 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".