Update on Ontario's water quantity management (policy, program and science) review
Bibliographic record
Abstract
Ontario's Government for the People is committed to preserving water for families now and for future generations. To achieve this Ontario is undertaking a thorough review of the province's water taking policies, programs and science tools to ensure that vital water resources are adequately protected and sustainably used in the face of a changing climate and continued population growth. Ontario has extended the moratorium on water taking permits by one year, now ending December 31, 2019, to allow time to complete this review and consult on any recommended enhancements. At the 2018 OGS-GSC Workshop, the ministry presented, "The Science behind Ontario's Water Quantity Management Review" and outlined key aspects of the water quantity science work being undertaken to ensure a robust and adaptive approach to water resources management into the future, and the water quantity scientific work being undertaken to improve our understanding of water resources knowledge on Ontario. The ministry's consultant, BluMetric Environmental Inc. (BMEI) presented an outline of water quantity science and jurisdictional reviews and water quantity assessments being undertaken. The Ministry will provide an update on the moratorium extension and the water quantity management review, particularly the science components and some of the findings of the BMEI project. As identified in the draft "Preserving and Protecting our Environment for Future Generations: A Made-in-Ontario Environment Plan" the focus moving forward will include examining approaches to assess and manage multiple water takings, establish priorities for different water uses, prepare and respond to drought conditions and ensure the knowledge gained through the drinking water source protection program helps inform our water management programs. (https://prod-environmental-registry.s3.amazonaws.com/2018-11/EnvironmentPlan_1.pdf)
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.
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 | 0.021 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.021 | 0.027 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".