Plagued by a Plethora of Peripherals: Refining Guidelines for Peripheral Taxa
Bibliographic record
Abstract
The size, location, and topography of British Columbia encourage incursions of taxa that are more widespread and abundant elsewhere. The periphery of the range of at least 1400 taxa extends into British Columbia. Over 900 of these appear on the Red and Blue Lists prepared by the Conservation Data Centre. Conversely, less than half of British Columbia's endemic taxa or taxa for which the province has significant global stewardship responsibility appear on the Red and Blue Lists. We examine why we conserve and list species, concluding that a primary scientific or practical reason is to sustain genetic variability. We consider two broad kinds of peripheral species—disjunct (geographically marginal) populations and politically peripheral (often ecological marginal) populations that straggle irregularly across provincial boundaries. We document the degree to which each enters provincial Red and Blue Lists. The Conservation Data Centre generates the Red and Blue Lists using seven ranking factors. These factors are correlated in a fashion that biases politically peripheral populations towards rankings of artificially high risk. Thus, the lists have little utility in guiding conservation priorities. Recovery plans for most politically peripheral species appear doomed to failure for sound biological reasons. We note alternative approaches to evaluating species for conservation action and recommend that conservation efforts for peripheral species be focused on disjunct populations, rather than politically peripheral populations.
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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 | 0.030 | 0.116 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".