Bibliographic record
Abstract
In Canada, aboriginal legacies in landscapes and their implications for land use planning for biodiversity conservation remain poorly acknowledged. Similarly, inter-cultural conversations on values about and priorities for biological resources and habitat protection remain under-developed. This essay begins with a rhetorical question. Will it be possible to forge successful ecosystem recovery strategies, to maintain all elements of local biological diversity through land use planning, without far deeper cognizance of the aboriginal legacies in Canadian landscapes? I do not think so. This discussion, from the drier enclaves on the south coast of British Columbia, centres on a federally funded ecosystem recovery team in the first four years of its operation from 1999 to 2003 and the near total lack of outreach to, and engagement with, aboriginal people and First Nations. These were the same years as the final phase of development of Canada’s relatively weak Species At Risk Act (SARA).2
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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.041 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.012 | 0.019 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".