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Record W4311922734 · doi:10.31234/osf.io/2hdyw

Spatial Context Scaffolds Long-Term Episodic Richness of Weaker Real-World Autobiographical Memories in Both Older and Younger Adults

2022· preprint· en· W4311922734 on OpenAlexafffund
Miranda Chang, Bryan Hong, Katarina Savel, Jialin Du, Melissa E. Meade, Chris B. Martin, Morgan D. Barense

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of TorontoBaycrest HospitalSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaUniversities Space Research AssociationJames S. McDonnell Foundation
KeywordsEpisodic memoryAutobiographical memoryRecallPsychologySpatial contextual awarenessContext (archaeology)Cognitive psychologyRetrospective memoryDevelopmental psychologyChildhood memoryCognitionHistoryComputer scienceNeuroscienceArtificial intelligence

Abstract

fetched live from OpenAlex

Remembering life events involves recalling not only what occurred (episodic details), but also where it took place (spatial context), both of which decline with age. Although spatial context can cue episodic detail recollection, it is unknown whether initially recalling an event alongside greater reinstatement of spatial context protects memory for episodic details in the long term, and whether this is affected by age. Here, we analysed 1079 personally-experienced, real-world events from 29 older adults and 12 younger adults. Events were recalled first on average 6 weeks after they occurred and then again on average 24 weeks after they occurred. We developed a novel scoring protocol to quantify spatial contextual details and used the established Autobiographical Interview to quantify episodic details. We found improved recall of episodic details after a delay if those details had initially been recalled situated in greater spatial context. Notably, for both older and younger adults, this preservation was observed for memories initially recalled with low, but not high, numbers of episodic details, suggesting that spatial context aided episodic retrieval for memories that required more support. This work supports the notion that spatial context scaffolds detail-rich event recollection and inspires memory interventions that leverage this spatial scaffold.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.000

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 head0.017
GPT teacher head0.312
Teacher spread0.295 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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