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Record W2326106868 · doi:10.1177/070674371506001204

What Do People Believe about Memory? Implications for the Science and Pseudoscience of Clinical Practice

2015· review· en· W2326106868 on OpenAlexaffvenue
Steven Jay Lynn, James Evans, Jean-Roch Laurence, Scott O. Lilienfeld

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2015
Typereview
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsConcordia University
Fundersnot available
KeywordsPseudosciencePsychologyMental healthPublic healthLaw enforcementPopulationSocial psychologyPsychiatryMedicineAlternative medicineLawNursingPolitical science

Abstract

fetched live from OpenAlex

We examine the evidence concerning what people believe about memory. We focus on beliefs regarding the permanence of memory and whether memory can be repressed and accurately recovered. We consider beliefs about memory among the undergraduate and general population, mental health professionals, judges, jurors, and law enforcement officers to provide a broad canvass that extends to the forensic arena, as well as to psychiatry, psychology, and allied disciplines. We discuss the implications of these beliefs for the education of the general public and mental health professionals regarding the science and pseudoscience of memory and the use of suggestive procedures in psychotherapy.

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)0.005
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.006
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.159
GPT teacher head0.451
Teacher spread0.291 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations50
Published2015
Admission routes2
Has abstractyes

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