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Record W4234105302 · doi:10.32920/ryerson.14651751.v1

Deviations from Bayes' Theorem During Belief Updating in Younger and Older Adults: Evidence From Behaviour and Neural Activity

2021· preprint· en· W4234105302 on OpenAlexaff
Bonnie Andrea Armstrong

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRepresentativeness heuristicHeuristicsBayes' theoremPsychologyCognitionCognitive psychologyYoung adultDevelopmental psychologyBayesian probabilitySocial psychologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Updating prior information with new information in accordance with Bayesian principles is a difficult task. Younger adult decision makers deviate from Bayes’ theorem by either overweighting prior information (i.e., using a conservatism heuristic) or overweighting new information (i.e., using a representativeness heuristic) on decision tasks without feedback. Similar to younger adults, older adults make decisions that require belief updating. Given agerelated decrements in cognitive control, older adults may be at a disadvantage compared with younger adults when updating beliefs. Prior research shows no age differences when making decisions under risk, however older adults perform worse than younger adults when making decisions under ambiguity. Currently it is unknown how older adults use heuristics when updating beliefs about risk and ambiguous information compared with younger adults. The primary aim of this dissertation was to examine age-related differences in the use of heuristics during belief updating, as well as the cognitive processes and neural correlates that underpin behaviour. In three experiments, younger and older adults completed a belief updating task with and without feedback using an urn-ball paradigm. The main results showed that both younger and older adults committed the representativeness error more than the conservatism error, with no age differences observed when updating beliefs without feedback but with younger adults updating beliefs more accurately than older adults with feedback. Further, age differences in the neural correlates that underlie belief updating showed evidence that older adults recruit additional resources in frontal regions of the brain to facilitate performance compared with younger adults. Event-related potentials showed evidence of cognitive control in response to conflicting information in both age groups, but a diminished neural response to feedback in older compared with younger adults. Additionally, while younger adults were not influenced by ambiguous information, older adults avoided committing the representativeness error only when new information was ambiguous. Last, individual differences in numeracy and cognitive reflection, but not thinking disposition, modulated belief updating performance. Together, the results show that younger and older adults can learn to update beliefs with feedback but with younger adults learning to a greater degree than older adults, especially when information is ambiguous.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.366
Teacher spread0.290 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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