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Record W4378070605 · doi:10.1111/jssr.12862

Masculinity, Femininity, and Reported Paranormal Beliefs

2023· article· en· W4378070605 on OpenAlexafffund
Tony Silva

Bibliographic record

VenueJournal for the Scientific Study of Religion · 2023
Typearticle
Languageen
FieldPsychology
TopicParanormal Experiences and Beliefs
Canadian institutionsUniversity of British Columbia
FundersScheme for Promotion of Academic and Research CollaborationUniversity of British Columbia
KeywordsParanormalFemininityPsychologyMasculinityExpression (computer science)Gender identitySocial psychologyGender rolePsychoanalysisMedicineAlternative medicine

Abstract

fetched live from OpenAlex

Abstract Previous research has found that women are more likely than men to report belief in nonmaterial paranormal phenomena (e.g., psychics). There are inconsistent findings about whether men are more likely than women to report belief in material paranormal phenomena (e.g., bigfoot/sasquatch), and no prior survey research has examined gender expression (as masculine or feminine) as it relates to paranormal beliefs. This paper asks: How do gender identity and gender expression relate to reported paranormal beliefs? It answers this question using a large sample ( n = 2504) of Canadians. Femininity helps explain differences between cisgender women and men on reported beliefs about foreseeing the future and telekinesis, but less so about reported belief in ghosts. Intriguingly, reported gender atypicality is associated with reported belief in all paranormal phenomena among cisgender women and among cisgender men. The results highlight the importance of measuring gender expression for beliefs that science cannot verify.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.395
Teacher spread0.311 · 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 designNot applicable
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

Citations11
Published2023
Admission routes2
Has abstractyes

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