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Record W2555109569 · doi:10.1080/08927936.2016.1228760

Development of the Partner’s Treatment of Animals Scale

2016· article· en· W2555109569 on OpenAlexaff
Amy Fitzgerald, Betty Barrett, Rachael Shwom, Rochelle Stevenson, Elena Chernyak

Bibliographic record

VenueAnthrozoös · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsNeglectAnimal welfareHarmPsychologyScale (ratio)Domestic violenceAnimal-assisted therapyPhysical abuseHUBzeroPsychological abuseClinical psychologySocial psychologyDevelopmental psychologyPet therapyPoison controlSuicide preventionPsychiatryMedicineEnvironmental healthEcologyGeographyBiology

Abstract

fetched live from OpenAlex

Although studies of the relationship between animal abuse and intimate partner violence have proliferated in recent years, building upon previous work and making cross-study comparisons have been rendered difficult by the utilization of differing operationalizations of animal maltreatment within this literature. This paper aims to mitigate this problem by introducing and detailing a scale of animal maltreatment by romantic partners, developed and tested with a sample of 55 women in domestic violence shelters who self-identified as victims of intimate partner violence. The Partner’s Treatment of Animals Scale (PTAS) is comprised of five scales (emotional animal abuse, threats to harm animals, animal neglect, physical animal abuse, and severe physical animal abuse) that have strong demonstrated reliability. The construction of the scales is presented in this paper, and recommendations are made for employing the PTAS in subsequent studies.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.368
Teacher spread0.330 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations22
Published2016
Admission routes1
Has abstractyes

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