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Record W4253793772 · doi:10.31234/osf.io/qys7d

Repetition increases perceived truth equally for plausible and implausible statements

2019· preprint· en· W4253793772 on OpenAlexaff
Lisa K. Fazio, David G. Rand, Gordon Pennycook

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsSocial Sciences and Humanities Research CouncilUniversity of Regina
Fundersnot available
KeywordsRepetition (rhetorical device)Statement (logic)PsychologyAffect (linguistics)Social psychologyTask (project management)Cognitive psychologyMechanism (biology)EpistemologyLinguisticsPhilosophyCommunication

Abstract

fetched live from OpenAlex

Repetition increases the likelihood that a statement will be judged as true. This illusory truth effect is well-established; however, it has been argued that repetition will not affect belief in unambiguous statements. When individuals are faced with obviously true or false statements, repetition should have no impact. We report a simulation study and a preregistered experiment that investigate this idea. Contrary to many intuitions, our results suggest that belief in all statements is increased by repetition. The observed illusory truth effect is largest for ambiguous items, but this can be explained by the psychometric properties of the task, rather than an underlying psychological mechanism that blocks the impact of repetition for implausible items. Our results indicate that the illusory truth effect is highly robust and occurs across all levels of plausibility. Therefore, even highly implausible statements will become more plausible with enough repetition.

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)0.006
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.087
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.087
GPT teacher head0.422
Teacher spread0.335 · 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 designObservational
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

Citations33
Published2019
Admission routes1
Has abstractyes

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