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Record W2095029705 · doi:10.1037//0096-3445.129.2.155

Divided attention and memory: Evidence of substantial interference effects at retrieval and encoding.

2000· article· en· W2095029705 on OpenAlexaff
Myra A. Fernandes, Morris Moscovitch

Bibliographic record

VenueJournal of Experimental Psychology General · 2000
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEncoding (memory)Encoding specificity principleTask (project management)RecallPsychologyWord (group theory)Cognitive psychologyInterference (communication)Interference theoryCommunicationSpeech recognitionCognitionComputer scienceWorking memoryNeuroscienceLinguistics

Abstract

fetched live from OpenAlex

In 5 divided attention (DA) experiments, students (24 in each experiment) performed visual distracting tasks (e.g., recognition of words, word and digit monitoring) while either simultaneously encoding an auditory word list or engaging in oral free recall of the target word list. DA during retrieval, using either of the word-based distracting tasks, produced relatively larger interference effects than the digit-monitoring task. DA during encoding produced uniformly large interference effects, regardless of the type of distracting task. Results suggest that when attention is divided at retrieval, interference is created only when the memory and concurrent task compete for access to word-specific representational systems; no such specificity is necessary to create interference at encoding. During encoding, memory and concurrent tasks compete primarily for general resources, whereas during retrieval, they compete primarily for representational systems.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.064
GPT teacher head0.372
Teacher spread0.308 · 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

Citations283
Published2000
Admission routes1
Has abstractyes

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