The importance of context in relation to policy transfer: a case study of environmental water allocation in Australia
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 Learning from the experiences of other jurisdictions has become a common strategy in the face of increasing severe environmental problems around the world. This phenomenon is very common in the water field, where surveys of institutions in other jurisdictions are widely used by practitioners to identify models that can be adopted. A precondition for success in policy transfer is careful consideration of the context within which institutions were developed. This paper explores the importance of context using the example of institutions for environmental water allocation (EWA) in the Murrumbidgee Catchment, in NSW, Australia. The case of EWA in the Murrumbidgee Catchment clearly demonstrates that, in the context of water policies, biophysical considerations must be considered alongside political, social, economic and cultural considerations when evaluating the extent to which water policies designed for one setting can be adopted elsewhere. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment.
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 | 0.000 |
| 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