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Record W2092804947 · doi:10.1002/acp.773

‘Please, remind me…’: The role of others in prospective remembering

2000· article· en· W2092804947 on OpenAlexafffund
Evelyn G. Schaefer, Michelle L. Laing

Bibliographic record

VenueApplied Cognitive Psychology · 2000
Typearticle
Languageen
FieldPsychology
TopicCognitive Functions and Memory
Canadian institutionsUniversity of Winnipeg
FundersUniversity of Winnipeg
KeywordsPsychologyCued speechProspective memorySocial psychologyCognitive psychologyNothingCognitionDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract In a study examining the effects of reminding expectations on prospective remembering, participants were asked to perform three internally and three externally cued tasks following a 30‐minute filler activity. Experimental participants were informed that at the time for performance they were to: remind another (confederate) participant about the tasks; receive a reminder about the tasks from the confederate; or both. Control participants heard nothing about reminders. Those led to expect a reminder performed significantly fewer tasks than did those who were not, regardless of whether they were to provide a reminder. Those expecting to provide a reminder performed more tasks than did those who were not, but this difference was only marginally significant. In all conditions, significantly more externally cued than internally cued tasks were performed. Reminding expectations appear to have affected retention of the content of to‐be‐performed tasks, rather than retention of the intent to perform them. The results are discussed in terms of modifications to the activation levels of the to‐be‐performed activities and/or to participants' self‐reminding strategies as a function of reminding expectations. Copyright © 2000 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)0.004
metaresearch head score (Gemma)0.028
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.307
Teacher spread0.293 · 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

Citations19
Published2000
Admission routes2
Has abstractyes

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