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Record W1991390655 · doi:10.5964/ejop.v4i1.422

Imagery and Emotion Components of Event Descriptions about Self and Various Others

2008· article· en· W1991390655 on OpenAlexaff
Nicholas A. Kuiper, Jennifer Kuindersma

Bibliographic record

VenueEurope’s Journal of Psychology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyCognitive psychologyEmotionalityCognitionEvent (particle physics)ReferentFocus (optics)Mental imageContrast (vision)Component (thermodynamics)Autobiographical memoryEvent-related potentialSocial psychologyComputer scienceArtificial intelligenceLinguistics

Abstract

fetched live from OpenAlex

Imagery and emotion have been identified as two of the main component systems of autobiographical events. It is not yet known, however, whether a primary focus on either the self or others may have an impact on these components. To investigate this issue, half of the participants in this study provide a real and made-up event description about themselves, and half provide descriptions about a well-known other. In addition, all participants generated a made-up event description about an unfamiliar other. In accord with predictions generated from a multiple-system model, real events received higher visual detail, imagability, and positive emotion ratings than made-up events. This pattern was also evident for a novel measure of imagery, in which real events were rated as being much more dynamic than made-up events. However, contrary to theoretical positions which postulate a special enhanced role for self-referent information processing, the self-descriptive events were not rated as being easier to imagine and did not have more positive emotions or visual detail, than descriptive events about well-known others. This pattern suggests that efficient cognitive schemata may be involved in the processing of information about both the self and well-known others. In contrast, descriptions of an unfamiliar other received lower imagery and emotionality ratings, suggesting that less well-differentiated cognitive structures are involved in component processing for these individuals.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.267

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)0.0000.000

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 head0.067
GPT teacher head0.321
Teacher spread0.254 · 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 designBench or experimental
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
Published2008
Admission routes1
Has abstractyes

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