Connecting people and places: the emerging role of network governance in large landscape conservation
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
The most important land and water issues facing North America and the world – including land‐use patterns, water management, biodiversity protection, and climate adaptation – require innovative governance arrangements. Most of these issues need to be addressed at several scales simultaneously, ranging from local to global. They require action at the scale of large landscapes given that the geographic scope of the issues often transcends the legal and geographic reach of existing jurisdictions and institutions. No single entity has the authority to address these types of cross‐boundary issues, resulting in gaps in governance and a corresponding need to create formal and informal ways work more effectively across administrative boundaries, land ownerships, and political jurisdictions. In response to this challenge, numerous models of “network governance” are emerging. These approaches vary in terms of purpose, spatial scale, composition, organization, and complexity. This article explains what network governance is, why it is emerging, how it compares to other models of natural resource governance, and the different ways in which it develops and evolves.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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