Challenges of assessing cetacean population recovery and conservation status
Bibliographic record
Abstract
ESR Endangered Species Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials ESR 6:173-184 (2008) - DOI: https://doi.org/10.3354/esr00102 Challenges of assessing cetacean population recovery and conservation status Milton M. R. Freeman* Canadian Circumpolar Institute, University of Alberta, Edmonton, Alberta T6G 2E1, Canada *Email: milton.freeman@ualberta.ca ABSTRACT: This paper examines the extent to which depleted whale populations have recovered (or not) and their perceived current conservation status and prognosis for continued survival, as represented in the International Union for Conservation of Nature and Natural Resources (IUCN) Red Lists. It is concluded that current hypothetical and untested predictions of extinction risk, while in many cases drawing attention to justifiable conservation needs, may seriously undervalue the resilience of species that have evolved to live in a dynamic and ever-changing reality including centuries of heavy exploitation by humankind. The paper questions the appropriateness of Red Listing criteria for long-lived highly mobile ocean-dwelling species that are scarcely affected by the principal threats upon terrestrial or aquatic species living in relatively restricted areas subject to habitat fragmentation and/or loss. This analysis draws attention to the problems associated with objectively assessing the conservation status of charismatic species and the value conflicts that may override evidence-based scientific conservation assessments. KEY WORDS: Whales · Whaling · Conservation · Population recovery · Predicting extinction · Red Listing · Charismatic species Full text in pdf format PreviousNextCite this article as: Freeman MMR (2008) Challenges of assessing cetacean population recovery and conservation status. Endang Species Res 6:173-184. https://doi.org/10.3354/esr00102 Export citation Mail this link - Contents Mailing Lists - RSS Facebook - Tweet - linkedIn Cited by Published in ESR Vol. 6, No. 2. Online publication date: December 30, 2008 Print ISSN: 1863-5407; Online ISSN: 1613-4796 Copyright © 2008 Inter-Research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".