Evidence map›Paper›PMID 41154842›Full record

ReviewBiology2025

Why Humans Prefer Phylogenetically Closer Species: An Evolutionary, Neurocognitive, and Cultural Synthesis.

Antonio Ragusa

Abstract readReview
In one paragraph

Review in Biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Antonio RagusaObstetrics and Gynecology Unit, Sassuolo Hospital, 41049 Sassuolo, Italy.ORCID 0000-0002-2579-1027

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans form deep attachments to some nonhuman animals, yet these attachments are unequally distributed across the tree of life. Drawing on evolutionary biology, comparative cognition, neuroscience, and cultural anthropology, this narrative review explains why empathy and affective preference are typically stronger for phylogenetically closer species-especially mammals-than for distant taxa such as reptiles, fish, or arthropods. We synthesize evidence that signal recognizability (faces, gaze, vocal formants, biological motion) and predictive social cognition facilitate mind attribution to mammals; conserved neuroendocrine systems (e.g., oxytocin) further amplify affiliative exchange, particularly in domesticated dyads (e.g., dog-human). Ontogenetic learning and media narratives magnify these effects, while fear modules and disgust shape responses to some distant taxa. Notwithstanding this average gradient, boundary cases-cephalopods, cetaceans, parrots-show that perceived agency, sociality, and communicative transparency can overcome phylogenetic distance. We discuss measurement (behavioral, psychophysiological, neuroimaging), computational accounts in predictive-processing terms, and implications for animal welfare and conservation. Pragmatically, calibrated anthropomorphism, hands-on education, and messaging that highlights agency, parental care, or ecological function reliably broaden concern for under-represented taxa. Recognizing both evolved priors and cultural plasticity enables more equitable and effective science communication and policy. Expanding empathy beyond its ancestral anchors is not only an ethical imperative but a One Health necessity: safeguarding all species means safeguarding the integrity of our shared planetary life.

Indexed as

affective preferenceanimal welfareconservation psychologydomesticationempathyoxytocinphylogenypredictive processing

Identifiers

PMID41154842
PMCPMC12561528

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.