Bibliographic record
Abstract
Abstract: Robust systems are characterized by a capacity to recover gracefully from the whole range of exceptional inputs and situations in a given environment. They have a connotation of elegance. This paper will highlight the importance of separating the different elements of any tradable property entitlement and allocation system into its component parts. The result is a constellation of institutional arrangements that can be expected to last, to withstand the test of time. Often, considerable reform is required to put in place robust systems. Using examples from Australia, this paper will highlight the importance of sequencing implementation of the reforms necessary to put robust systems in place. Robustness is achieved by using three instruments rather than one instrument to allocate water and control use, and coupling these three instruments with three separate planning instruments. Résumé: Les systèmes robustes se caractérisent par la capacité de se remettre progressivement d’un éventail complet de situations et d’entrées exceptionnelles dans un contexte donné. Ils possèdent une connotation d’élégance. La présente communication soulignera l’importance de la division, en parties constituantes, des différents éléments de tout droit de propriété négociable et du système de répartition. Il en résulte une constellation d’arrangements institutionnels qui en temps normal devraient s’avérer durables et résister à l’épreuve du temps. Souvent, la mise en place de systèmes robustes demande des
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".