Analysis Of Recovery Strategies For Boreal Woodland Caribou Populations In The Cold Lake And Little Smoky Regions Of Alberta
Bibliographic record
Abstract
The oil and gas industry is an integral component of Alberta’s economic well-being. The boreal forest is home to caribou and many of its ranges intersect at sites of industrial development in Alberta. The boreal woodland caribou (Rangifer tarandus caribou) is currently listed as threatened under the Canada Species at Risk Act and Alberta Wildlife Act. This research study evaluates three potential caribou recovery strategies: habitat restoration, predator control, and policy and land-use planning that could be applied to the Cold Lake and Little Smoky herds in Alberta. The first phase of the research project included a detailed literature review to gain a thorough understanding of caribou management. The second phase included targeted interviews with experts in caribou management including individuals from Alberta government, academia, industry, and non-governmental organization. All groups except the Alberta government respondents felt that the current regulations for recovery strategies lacked political will, whereas Alberta government representatives seemed more concerned with meeting the statutory caribou protection measures required under the federal Species at Risk legislation. Overall, the management tools were perceived to be essential but need to be applied on a case-by-case basis. The main recommendation from the research project is that stronger collaboration, improved enforcement of mitigation tools, and clear rules and direction by the provincial government are needed for the sustainability of woodland caribou populations in Alberta.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".