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Record W4283834804 · doi:10.1177/17506980221108476

Living in history and by the cultural life script: What events modulate autobiographical memory organization in a sample of older adults from Romania?

2022· article· en· W4283834804 on OpenAlexaff
Alexandra M. Opriș, Laura Visu‐Petra, Norman Brown

Bibliographic record

VenueMemory Studies · 2022
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of Alberta
FundersUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii
KeywordsAutobiographical memoryPsychologyAffect (linguistics)Sample (material)Childhood memoryDevelopmental psychologyHistoryEpisodic memoryCognitive psychologyRecallCognitionCommunication

Abstract

fetched live from OpenAlex

In the current study, we investigated the organization of autobiographical memory in view of the Living-in-History effect, which is visible when personal memory and historical memory become intertwined. We investigated how often participants dated their own personal recollections with reference to important historical events (such as the Fall of Communism). Furthermore, we also examined whether cultural life script events served as a prominent strategy to date personal memories in our sample of 35 participants ( Mage = 69.76 years, SD = 8.26). This study failed to document the Living-in-History effect, as participants mentioned only few historical events of interest to this study when dating their personal memories. In addition, supporting the Cultural Life Script theory, participants employed culturally transmitted knowledge to navigate through their autobiographical memories. We conclude that for our sample, historically defined autobiographical memories mainly develop when the specific public events affect in a dramatic manner the individuals’ lives.

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)0.004
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.022
GPT teacher head0.270
Teacher spread0.248 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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