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Record W3163510559 · doi:10.31234/osf.io/d8s5a

Does belief in free will influence biological motion perception?

2021· preprint· en· W3163510559 on OpenAlexafffund
Wei Peng, Emiel Cracco, Nikolaus F. Troje, Marcel Braß

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicFree Will and Agency
Canadian institutionsYork University
FundersCanada First Research Excellence FundVlaamse regeringChina Scholarship CouncilFonds Wetenschappelijk Onderzoek
KeywordsBiological motionPerceptionDualismMotion (physics)PsychologyDeterminismSocial psychologySocial perceptionCognitive psychologyFree willJust-world hypothesisEpistemologyComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Previous research suggests that belief in free will correlates positively with intention perception. However, whether belief in free will is also related to more basic social processes is unknown. Based on evidence that biological motion is an intention-carrier, we investigate if belief in free will and related two beliefs, namely belief in dualism and belief in determinism, are associated with biological motion perception. Signal Detection Theory (SDT) was used to measure participants’ ability to detect biological motion from scrambled background noise (d') and their response bias (c) in doing so. In two experiments, we found that belief in determinism and belief in dualism, but not belief in free will, were associated with the perception of biological motion. However, no causal relationship was found when experimentally manipulating free will-related beliefs. In general, our research suggests that basic social processes, like biological motion perception, can be predicted by high-level beliefs.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.268
Teacher spread0.235 · 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 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

Citations0
Published2021
Admission routes2
Has abstractyes

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