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Record W2060224054 · doi:10.2190/ic.31.4.f

Predictors of Adult Narrative Elaboration: Emotion, Attachment, and Gender

2012· article· en· W2060224054 on OpenAlexaff
Allyssa McCabe, Carole Peterson

Bibliographic record

VenueImagination Cognition and Personality · 2012
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsElaborationPsychologyDevelopmental psychologyNarrativeAutobiographical memoryAnxietyCognitive psychologyRecall

Abstract

fetched live from OpenAlex

When individuals first converse with others, they bring to those interactions expectations and habits of communication that are affected by many factors. In this study we looked at several factors simultaneously to see which predicted narrative elaboration in personal memories of early childhood and adolescence: self-described attachment patterns, stress of original experiences, and gender. A sample of 195 undergraduates aged 18–29 recalled their very earliest memory and their earliest memory of adolescence (in counterbalanced order) and completed the Multi-Item Measure of Romantic Attachment (Brennan, Clark, & Shaver, 1998). Positive experiences dominated both early and adolescent memories, though there were significant positive correlations between ratings of negativity (stress) and several measures of narrative elaboration in both kinds of memories. Avoidance scales correlated negatively with many measures of elaboration, while anxiety scales correlated positively only with one submeasure. In regression analyses of narrative elaboration conducted separately for early and late memories, the following significant patterns were observed: (1) females elaborated more than males; (2) more negative memories predicted more elaboration but only in early memories; and (3) avoidance scores predicted less elaboration, while anxiety scales were not significant predictors. Results are discussed in terms of the consequences of these issues for dating.

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)0.000
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 score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.362
Teacher spread0.323 · 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

Citations6
Published2012
Admission routes1
Has abstractyes

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