MétaCan
Menu
Back to cohort
Record W2152729183 · doi:10.1002/acp.1023

Going shopping and identifying landmarks: does collaboration improve older people's memory?

2004· article· en· W2152729183 on OpenAlexafffund
Michael G. Ross, Steven J. Spencer, Lisa Linardatos, Kent C. H. Lam, Mihailo Perunovic

Bibliographic record

VenueApplied Cognitive Psychology · 2004
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Waterloo
FundersCanadian Institutes of Health Research
KeywordsRecallPsychologyCertaintyLandmarkSocial psychologyCognitive psychologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Abstract Older participants (mean age = 72.82 years) attempted to recall items from shopping lists while shopping in a supermarket and subsequently in their homes on recognition tests. They also attempted to identify local landmarks on a map. The recall occurred either together with their spouses or independently. Collaborative recall was compared to the pooled, nonredundant recall of spouses who completed the memory tasks alone (nominal groups). Nominal groups produced more hits on most measures and never fewer hits than did collaborative groups. However, collaborative groups consistently generated fewer memory errors than did nominal groups. In many everyday contexts, a tendency for collaboration to reduce false recall could be advantageous to older people. Signal detection analyses revealed that collaboration leads couples to require a higher level of certainty before they are willing to claim that they recognize an item. Finally, we examined the relation between expertise and recall in the shopping and landmark tasks. Copyright © 2004 John Wiley & Sons, Ltd.

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)0.011
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.328
Teacher spread0.305 · 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

Citations95
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueApplied Cognitive PsychologySame topicMemory Processes and InfluencesFrench-language works237,207