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Record W3189142417 · doi:10.1073/pnas.2106640118

The Medusa effect reveals levels of mind perception in pictures

2021· article· en· W3189142417 on OpenAlexafffund
Paris Will, Elle Merritt, Rob Jenkins, Alan Kingstone

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2021
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British Columbia
FundersBritish AcademySocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsPerceptionStimulus (psychology)PsychologyCognitive psychologyAttributionAbstractionSocial psychologyCommunicationEpistemologyPhilosophyNeuroscience

Abstract

fetched live from OpenAlex

Throughout our species history, humans have created pictures. The resulting picture record reveals an overwhelming preference for depicting things with minds. This preference suggests that pictures capture something of the mind that is significant to us, albeit at reduced potency. Here, we show that abstraction dims the perceived mind, even within the same picture. In a series of experiments, people were perceived as more real, and higher in both Agency (ability to do) and Experience (ability to feel), when they were presented as pictures than when they were presented as pictures of pictures. This pattern persisted across different tasks and even when comparators were matched for identity and image size. Viewers spontaneously discriminated between different levels of abstraction during eye tracking and were less willing to share money with a more abstracted person in a dictator game. Given that mind perception underpins moral judgement, our findings suggest that depicted persons will receive greater or lesser ethical consideration, depending on the level of abstraction.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.128
GPT teacher head0.352
Teacher spread0.223 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicPsychology of Moral and Emotional JudgmentFrench-language works237,207