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Record W3097868833 · doi:10.1136/medethics-2020-106894

Emotional support animals are not like prosthetics: a response to Sara Kolmes

2020· letter· en· W3097868833 on OpenAlexaff
Jessica du Toit, David Benatar

Bibliographic record

VenueJournal of Medical Ethics · 2020
Typeletter
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsWestern University
Fundersnot available
KeywordsFunction (biology)Human bodyPsychologyEmotional supportInternet privacySocial psychologyComputer scienceSocial supportArtificial intelligence

Abstract

fetched live from OpenAlex

Sara Kolmes has argued that the human 'handlers' of emotional support animals (ESAs) should have the sorts of body-like rights to those animals that people with prosthetics have to their prosthetics. In support of this conclusion, she argues that ESAs both function and feel like prosthetics, and that the disanalogies between ESAs and prosthetics are irrelevant to whether humans can have body-like rights to their ESAs. In response, we argue that Ms Kolmes has failed to show that ESAs are body-like in the ways that paradigmatic prostheses are and that, even if they were, these similarities would be outweighed by a crucial dissimilarity that she underestimates.

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)0.010
metaresearch head score (Gemma)0.174
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.164
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.174
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0040.039
Insufficient payload (model declined to judge)0.0030.001

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 head0.184
GPT teacher head0.403
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2020
Admission routes1
Has abstractyes

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