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Record W2042392563 · doi:10.1037/a0017122

Learning to bypass the central bottleneck: Declining automaticity with advancing age.

2010· article· en· W2042392563 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePsychology and Aging · 2010
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutomaticityBottleneckPsychologyTask (project management)Cognitive psychologyCognitionYoung adultAudiologyDevelopmental psychologyNeuroscienceComputer science

Abstract

fetched live from OpenAlex

Does advancing age reduce the ability to bypass the central bottleneck through task automatization? To answer this question, the authors asked 12 older adults and 20 young adults to first learn to perform an auditory-vocal task (low vs. high pitch) in 6 single-task sessions. Their dual-task performance was then assessed with a psychological refractory period paradigm, in which the highly practiced auditory-vocal task was presented as Task 2, along with an unpracticed visual-manual Task 1. Converging evidence indicated qualitative differences in dual-task performance with age: Whereas the vast majority of young adults bypassed the bottleneck, at most 1 of the 12 older adults was able to do so. Older adults are either reluctant to bypass the bottleneck (as a matter of strategy) or have lost the ability to automatize task performance.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.373
Teacher spread0.358 · 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