Deconstructing compassionate conservation
Bibliographic record
Abstract
Compassionate conservation focuses on 4 tenets: first, do no harm; individuals matter; inclusivity of individual animals; and peaceful coexistence between humans and animals. Recently, compassionate conservation has been promoted as an alternative to conventional conservation philosophy. We believe examples presented by compassionate conservationists are deliberately or arbitrarily chosen to focus on mammals; inherently not compassionate; and offer ineffective conservation solutions. Compassionate conservation arbitrarily focuses on charismatic species, notably large predators and megaherbivores. The philosophy is not compassionate when it leaves invasive predators in the environment to cause harm to vastly more individuals of native species or uses the fear of harm by apex predators to terrorize mesopredators. Hindering the control of exotic species (megafauna, predators) in situ will not improve the conservation condition of the majority of biodiversity. The positions taken by so-called compassionate conservationists on particular species and on conservation actions could be extended to hinder other forms of conservation, including translocations, conservation fencing, and fertility control. Animal welfare is incredibly important to conservation, but ironically compassionate conservation does not offer the best welfare outcomes to animals and is often ineffective in achieving conservation goals. Consequently, compassionate conservation may threaten public and governmental support for conservation because of the limited understanding of conservation problems by the general public.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.137 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.006 | 0.011 |
| 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".