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Animal Moral Psychologies

2022· book-chapter· en· W4224307730 on OpenAlexaff
Susana Monsó, Kristin Andrews

Bibliographic record

VenueOxford University Press eBooks · 2022
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsYork University
Fundersnot available
KeywordsMoralityAutonomyMoral disengagementSocial cognitive theory of moralityNormativeFoundation (evidence)Agency (philosophy)Moral agencyEpistemologyMoral reasoningMoral developmentMoral psychologyEmpathyAction (physics)Environmental ethicsSociologySocial psychologyPsychologyPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

Abstract Observations of animals engaging in apparently moral behaviour have prompted the question of whether morality is shared between humans and other animals, with little agreement on the answer. Some philosophers explicitly argue that morality is unique to humans, because moral agency requires capacities that are only demonstrated in our species. Other philosophers argue that some animals can participate in morality because they possess these capacities in a rudimentary form, or because the touted capacities are not necessary for moral participation. Empirical research programs on possible moral capacities such as fairness and empathy have seen scientists joining in these debates. We argue that the current debate suffers because discussions often fail to provide both a proper philosophical foundation about the nature of moral practices and a solid empirical ground for claims about what animals can and cannot do. In this chapter we focus on the second of these issues, and defend the claim that animals have three sets of capacities that, on some views, are taken as necessary or foundational for moral judgment and action. These are capacities of care, capacities of autonomy, and normative capacities. Care, we argue, is widely found among social animals. Autonomy and normativity are more recent topics of empirical investigation, so while there is less evidence of these capacities at this point in our developing scientific knowledge, the current data is strongly suggestive.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.832
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.045
GPT teacher head0.291
Teacher spread0.246 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations12
Published2022
Admission routes1
Has abstractyes

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