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Record W4281663269 · doi:10.31234/osf.io/su3nq

Intuition, reason, and conspiracy beliefs

2022· preprint· en· W4281663269 on OpenAlexafffund
Jabin Binnendyk, Gordon Pennycook

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsUniversity of Regina
FundersSocial Sciences and Humanities Research Council of CanadaJohn Templeton Foundation
KeywordsIntuitionSkepticismMisinformationEpistemologyPsychologySocial psychologyCognitionPhilosophyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Conspiracy theories tend to involve doubt and skepticism, but are conspiracy believers really more deliberative? We review recent research that investigates the relative roles of intuition and reason in conspiracy belief and find that the preponderance of evidence indicates that conspiracy belief is linked to an overreliance on intuition and a lack of reflection. This research, in addition to work investigating the broader influence of misinformation, indicates that people may believe conspiracies partly because they fail to engage in analytic thinking and rely too much on their intuitions. However, we also note that research in this area lacks in experimental studies and that work focusing on underlying cognitive mechanisms is needed.

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)0.044
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 score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.009
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.367
Teacher spread0.325 · 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

Citations10
Published2022
Admission routes2
Has abstractyes

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