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Record W3188547372 · doi:10.1177/0956797621998316

Aging Impairs Inhibitory Control Over Incidental Cues: A Construal-Level Perspective

2021· article· en· W3188547372 on OpenAlexaff
Liat Hadar, Yaacov Trope, Boaz M. Ben‐David

Bibliographic record

VenuePsychological Science · 2021
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersJeremy Coller FoundationUnited States - Israel Binational Science Foundation
KeywordsPsychologyConstrual level theoryPerspective (graphical)Young adultCognitionDevelopmental psychologyControl (management)Cognitive psychologySocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

Age-related changes in decision making have been attributed to deterioration of cognitive skills, such as learning and memory. On the basis of past research showing age-related decreases in the ability to inhibit irrelevant information, we hypothesize that these changes occur, in part, because of older adults’ tendency to give more weight to low-level, subordinate, and goal-irrelevant information than younger adults do. Consistent with this hypothesis, our findings demonstrated that young adults are willing to pay more for a product with superior end attributes than a product with superior means attributes (Study 1, N = 200) and are more satisfied after an experience with superior end than means attributes (Study 2, N = 399). Young adults are also more satisfied with a goal-relevant than with a goal-irrelevant product (Study 3, N = 201; Study 4, N = 200, preregistered). Importantly, these effects were attenuated with age. Implications for research on construal level and aging, as well as implications for policymakers, are discussed.

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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.087
GPT teacher head0.466
Teacher spread0.379 · 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 teacher head, not a consensus.

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

Citations11
Published2021
Admission routes1
Has abstractyes

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