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Record W1987555203 · doi:10.1080/00221325.2013.869534

Empathy and Autobiographical Memory: Are They Linked?

2014· article· en· W1987555203 on OpenAlexaff
Franca Tani, Carole Peterson, Andrea Smorti

Bibliographic record

VenueThe Journal of Genetic Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAutobiographical memoryEmpathyPsychologyCognitive psychologySocial psychologyRecall

Abstract

fetched live from OpenAlex

Autobiographical memory and empathy have been linked with social interaction variables as well as gender in independent bodies of literature. However a scarcity of research exists on the direct link between autobiographical memory and empathy. Exploring this link, in particular for memory of friendships and empathy, was the authors' main aim. A total of 107 Italian undergraduates participated. A memory fluency task was used to assess accessibility of memories spanning their entire life (preschool through university) and an empathy scale (Italian version of the Interpersonal Reactivity Index) was employed to measure the participants' level and dimensions of empathy. For men, empathy scores were related to how many memories they could recall. Specifically, men with higher scores on the fantasy and empathic concern scales and those with lower scores on the personal distress scales recalled more memories of friends. However, affective quality of their memories was unrelated to empathy. In contrast, for women there was no relationship between number of memories and empathy, but the emotional tone of their memories was related to empathy: those with higher scores on the personal distress scale had proportionately fewer affectively positive memories. Results are discussed in terms of gender differences in both empathy and parental socialization patterns.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.458
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.323
Teacher spread0.300 · 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.

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

Citations15
Published2014
Admission routes1
Has abstractyes

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