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Record W4389341638 · doi:10.3389/fvets.2023.1329398

Editorial: Exploring cats: their behaviors and human-cat interactions

2023· editorial· en· W4389341638 on OpenAlexaboutno aff
Emma K. Grigg, Dennis C. Turner, Leslie A. Lyons, Benjamin L. Hart, Lynette A. Hart

Bibliographic record

VenueFrontiers in Veterinary Science · 2023
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCATSBiologyZoologyComputer science

Abstract

fetched live from OpenAlex

Over 45 million US households contain at least one companion cat (2); in the European Union, the population of pet cats is estimated to be 113 million (outnumbering the estimated 92 million dogs) (1). Despite this global popularity, research into the behavior and welfare of cats living in private homes is still limited; and arguably, even less is known about the mechanisms of human-cat interactions within the home. Outside the home, cats allowed uncontrolled outdoor access, alongside free-roaming cat colonies outside of human ownership (but not always without human care), still generate considerable controversy between animal advocates and conservationists concerned about cats' impact on wildlife. This Research Topic presents 12 new papers that shed light on these issues and more. The goal of this special issue is to improve our understanding of companion cats, with particular focus on their interactions with humans, and human attitudes towards these animals. The twelve manuscripts in this special issue on cat behaviors and the development of the human-cat bond cover a wide variety of themes.Turner presents a mini-review of the available literature on a number of topics relevant to our understanding of human-cat interactions, such as the importance of kitten socialization, how cats communicate with their humans, and the mechanics of social interactions between cats and humans (such as the influence of who initiates contact, and of symmetry in compliance, or lack of compliance, with the partner's "wishes"). Noting the importance of ensuring the animals' wellbeing during human-cat interactions (and the scarcity of research into this issue with companion cats), Haywood et al. present Human-Cat Interaction guidelines designed to improve the comfort and welfare of companion cats during such interactions. They developed and tested the efficacy of these new guidelines with 100 shelter cats, interacting with 120 novel members of the public, and report their results here. Nagasawa et al. examine physiological (urinary oxytocin and cortisol) responses to interaction with humans, by comparing these variables in cats during positive interactions with a familiar caretaker (including physical contact, play, etc.), versus. when such interactions were removed. In another study using physiological (fecal cortisol) measures of stress, along with weight and behavior, Carlisle et al. investigate stress levels of cats adopted by families of children with autism spectrum disorder (ASD). Cats in the Carlisle et al. study were specifically selected for sociability and calmness using the validated Feline Temperament Profile, and the adopters provided with education on cat behavior; the authors discuss the importance of these factors to successful adoption into these homes.Gajdoš Kmecová et al. review and seek to extend the existing research on play in cats, much of which has focused to date on object play [e.g., (3)], by looking at social play between cats. They suggest using a psychobiological approach to the study of play, which considers the motivational and emotional states of the cats; and present an ethogram (synthesized from the literature) and common terminology for use in future studies of cat social play. Khoddami et al. also seek to extend the existing literature on interactions between cats in multi-cat homes, by focusing specifically on two-cat households. They note that previous studies frequently lack focus on any particular group size, limiting our understanding of social dynamics in specific group sizes, despite the fact that most multi-cat households in the US and Canada consist of two cats (4,5).Four papers in this issue focus on free-roaming cats, with two exploring the often-contentious issue of domestic cats' impact on wildlife. Tan et al. summarize the arguments for and against allowing cats outdoor access, and identify several owner-and cat-related factors associated with allowing companion cats uncontrolled access to the outdoors. Kim et al. investigate attitudes of different demographic groups towards feral cats in Seoul, South Korea, following the establishment of government-supported cat feeding stations around that city. They report distinct and sometimes complex differences between the groups in their attitudes towards cats and their preferred management approach for feral cat populations [e.g., trap-neuter-release (TNR) vs. culling]; they also discuss the possible impact of the feeding stations on these results. Turner takes a critical look at the literature on cats' impacts on wildlife, in light of recent media reports of the "alarming predation of house cats on prey populations". Turner cautions that researchers should avoid bias and misinterpretation of field data, by considering what is known about predatory behavior in domestic cats and reporting estimates of total prey species population sizes. In their paper examining human-cat interactions involving free-living cats, Wandesforde-Smith et al. note the 'moral pluralism' involved in the emphasis (even requirement) for humane care and protection of owned companion cats, alongside the systematic culling of large numbers of cats supported by public policy.The final two papers discuss research into new use of technology in the study of domestic cats. Xu et al. apply and advocate for machine learning techniques (in contrast to the more traditional biomechanical experiments with living cats or cat cadavers) for improving our understanding of the feline 'athletic ability'. Given recent work using heart rate variability (HRV) as an indicator of emotion in non-human animals [e.g., (6)], Grigg et al. compare HRV data collected using an affordable, commercially available cardiac monitoring system (Polar H10) against data from a traditional ambulatory electrocardiogram, to assess whether the Polar monitors could be used for this purpose in unrestrained cats.This special issue tackles a broad range of topics relevant to domestic cats. Many of the papers add particular insight into our understanding of human-cat, and cat-cat, interactions. Others report on issues important to cat welfare, such as controversies surrounding outdoor cats and wildlife. Our understanding of domestic cat behavior and human-cat interactions continues to improve, as these papers demonstrate.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.138
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.049
GPT teacher head0.377
Teacher spread0.328 · 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
GenreEditorial

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

Citations6
Published2023
Admission routes1
Has abstractyes

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