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Record W4366091138 · doi:10.1080/21550085.2023.2200728

Wild Animal Ethics: A Freedom-Based Approach

2023· article· en· W4366091138 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEthics Policy & Environment · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsUniversité de Montréal
FundersAgència de Gestió d'Ajuts Universitaris i de RecercaFundação para a Ciência e a TecnologiaUniversité de Montréal
KeywordsAnimal ethicsOrder (exchange)Freedom of choiceAnimal rightsControl (management)Environmental ethicsPsychological interventionLaw and economicsPolitical scienceLawSociologyPsychologyComputer sciencePhilosophyEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

On expectation, most wild animals have lives of net suffering due to naturogenic causes. Some have claimed that concern for their well-being gives us reasons to intervene in nature on their behalf. Against this, it has been said that many interventions to assist wild animals would be wrong, even if successful, because they would violate their freedom. According to the Freedom-based Approach I defend in this paper, this view is misguided. Concern for wild animal freedom does indeed gives us reasons to secure these animals against control-undermining interferences, but also to intervene in nature in order to enrich their choices.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.014

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.

Opus teacher head0.080
GPT teacher head0.313
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it