Bibliographic record
Abstract
Wetlands play a crucial role in buffering the effects of climate change and supporting climate adaptation and resiliency. Sustainable wetland management practices require integration into the water sector to address economic, social and environmental factors, and to address urgent contemporary complex environmental problems such as climate change. Canada’s boreal forest and boreal region affect the health of the environment worldwide by storing carbon, purifying air and water, and regulating the climate. This thesis examines Alberta’s Wetland Policy (2013) design and implementation to assess the policy’s potential to effectively conserve, restore, protect, and manage Alberta’s wetlands in order to sustain the benefits they provide to the environment, society, and economy. Transition to a province-wide wetland policy requires a foundation that integrates water resources management—made possible by the Government of Alberta’s regional land-use planning framework. An analytical framework was derived from and applied to the Alberta context (as described in Alberta government documents, supplemented by key informant experience) to examine the policy and its implementation in relation to the wise use of wetland management practices. Results indicate that Alberta tends to opt for mitigation and compensation for wetland development rather than wetland retention. There is potential for increasing the conservation of wetlands. The policy and legislative framework could support the wise use of wetlands, but there are substantial gaps in implementation. Recommendations will stress the need for functional integration across government ministries to identify ecological threshold limits and better communication with, and support for, municipalities and landowners, particularly agriculturalists.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".