WHY ANIMAL WELFARE IS NOT BIODIVERSITY, ECOSYSTEM SERVICES, OR HUMAN WELFARE: TOWARD A MORE COMPLETE ASSESSMENT OF CLIMATE IMPACTS
Bibliographic record
Abstract
Taking the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) as representative, I argue that animal ethics has been neglected in the assessment of climate policy. While effects on ecosystem services, biodiversity, and human welfare are all catalogued quite carefully, there is no consideration at all of the effects of climate change on the welfare of animals. This omission, I argue, should bother us, for animal welfare is not adequately captured by assessments of ecosystem services, biodiversity, or human welfare. After describing the paper’s assumptions and discussing the role of the IPCC’s Assessment Reports in climate policy, I consider the presentation of climate impacts in the IPCC’s Fifth Assessment Report, noting the aspects of animal welfare that are (and are not) considered there, and comparing the report’s treatment of animal welfare to its treatment of human welfare. Next, I argue that the concepts of ecosystem services, biodiversity, and human welfare do not adequately capture the welfare of animals. Finally, I discuss concerns about human responsibility for animal welfare and the practicality of including considerations of animal welfare among the climate impacts studied by the IPCC.
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 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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".