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Record W1978928363 · doi:10.2224/sbp.2003.31.6.585

DO PSYCHOLOGY COURSES REDUCE BELIEF IN PSYCHOLOGICAL MYTHS?

2003· article· en· W1978928363 on OpenAlexaff
Lionel Standing, Herman Huber

Bibliographic record

VenueSocial Behavior and Personality An International Journal · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsBishop's University
Fundersnot available
KeywordsMythologyPsychologySkepticismMainstreamSocial psychologyPopular psychologyEducational psychologySchool psychologyPsychological researchAsian psychologyPedagogyEpistemologyPsychology, Philosophy and Physiology

Abstract

fetched live from OpenAlex

This study examined the degree to which psychology students accept popular psychology myths that are rejected by mainstream researchers (e.g., “people use only 10% of their brain's capacity”), and the effect of psychology courses on myth acceptance. Using a 20-item, true-false myth belief questionnaire, it examined the levels of gullibility among 94 undergraduates at different stages of their education, and related these to their educational and demographic backgrounds. High overall levels of myth acceptance (71%) were found, in line with earlier research. Myth acceptance decreased with the number of psychology courses that students had taken in university, but increased with the number that they had taken in junior college. Belief in myths was lower among students who were majoring in psychology, were older, had higher grades, and had advanced training in research methods, but it was not related to gender, geographical origin, or university year. It is concluded that university courses appear beneficial in encouraging methodological skepticism, whereas taking specialized psychology courses in junior college may hinder rather than promote critical thinking among undergraduates.

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)0.013
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.130
GPT teacher head0.509
Teacher spread0.378 · 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

Citations59
Published2003
Admission routes1
Has abstractyes

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