Legitimacy assessment throughout the life of collaborative water governance
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
Abstract Collaborative governance arrangements involving a diversity of groups (e.g., governments, civil society, industry) are increasingly being used to make decisions or give advice to decision‐makers on water issues. Legitimacy is a critical factor for the effectiveness, efficiency, stability, and popular approval of collaborative efforts. However, as a concept, legitimacy remains contested with various meanings, theoretical backgrounds, and source norms. Clarity is particularly needed around the changing sources of legitimacy as collaborative efforts mature. Drawing on case‐study research of five collaborations in British Columbia, Canada, we present a framework of legitimacy sources as collaborations evolve. Legitimacy during the establishment of a collaboration depends principally on community readiness to collaborate, a sense of need, and the perceived potential for goal achievement. As a collaboration continues to grow, its legitimacy forms mainly from normative processes—the perceived quality of factors such as accountability, transparency, consensus‐building, and representation of relevant discourses. Once a collaboration reaches maturity and faces questions of its future existence, legitimacy is largely result‐based—tangible and contextually meaningful outcomes must be easily identifiable and promoted. Increased understanding of the dynamics of legitimacy can help collaborative efforts strategically plan and work toward their goals as they evolve.
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