An evaluation of Ontario's water allocation system, the perspectives of water users
Bibliographic record
Abstract
This thesis is an investigation of Ontario's water allocation system. Water is essential for human survival and activities, yet the quantity of water available is periodically exceeded by demands. Thus, jurisdictions throughout the world have utilized water allocation systems to resolve issues regarding the access to water. In Ontario, common law doctrine, the 'Permit to Take Water Program' and other legislation dictate the allocation of water among users. The existing system was analyzed using water users' perspectives from two case study areas in southern Ontario. The existing water allocation system was found to be limited by water availability and use knowledge and data, constrained by current monitoring methods, unclear, enforced inconsistently, poorly communicated between stakeholders, and provided little or no security to water users. Moreover, development of explicit allocation rules, establishment of water use priorities, improvements in water use planning and development, enhancement of communication, cooperation and coordination between stakeholders, and strengthening of monitoring and enforcement were all suggested by water users as ways to improve the existing water allocation system.
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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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".