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Record W4391951280 · doi:10.1159/000537938

How Not to Find Over-Imitation in Animals

2024· article· en· W4391951280 on OpenAlex
Jedediah W.P. Allen, Kristin L. Andrews

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHuman Development · 2024
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsImitationPsychologyCognitive psychologyDevelopmental psychologyCognitive scienceSocial psychology

Abstract

fetched live from OpenAlex

While more species are being identified as cultural on a regular basis, stark differences between human and animal cultures remain. Humans are more richly cultural, with group-specific practices and social norms guiding almost every element of our lives. Furthermore, human culture is seen as cumulative, cooperative, and normative, in contrast to animal cultures. One hypothesis to explain these differences is grounded in the observation that human children across cultures appear to spontaneously over-imitate silly or causally irrelevant behaviors that they observe. The few studies on over-imitation in other species are largely taken as evidence that spontaneous over-imitation is not present in other species. This leads to <i>the over-imitation hypothesis</i> – that the differences between human culture and animal cultures can be traced to the human unique tendency to over-imitate. In this paper, we analyze the current state of the literature on animal over-imitation and challenge the adequacy of the over-imitation hypothesis for the differences between humans and animal cultures. To make this argument, we first argue that the function of human over-imitation is norm-learning and that over-imitation, like skill-learning, should be subject to selective social learning effects. Then we review the empirical evidence against animal over-imitation and argue that these studies do not take into account the relevant variables given the normative and selective nature of over-imitation. We then analyze positive empirical evidence of over-imitation in great apes and canids from the experimental literature and conclude that the current body of evidence suggests that some canids and primates may have the capacity for over-imitation. This paper offers a methodological suggestion for how to study animal over-imitation, and a theoretical suggestion that over-imitation might be much more widely found among species. The larger implication for claims about human uniqueness suggests that if we do find widespread evidence of over-imitation across species, many of the current theories of human uniqueness that focus on human hyper-cooperation or social norms may have only identified a difference of degree, not of kind, between humans and other animals.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.816
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.089
GPT teacher head0.385
Teacher spread0.295 · 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