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Record W3021416377

Recalling Mixed Emotions

2008· article· en· W3021416377 on OpenAlexaff
Jennifer Aaker, Aimée Drolet, Dale Griffin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRecallPsychologyAffect (linguistics)Longitudinal fieldCognitive psychologyAssociation (psychology)Episodic memorySocial psychologyCognitionCommunication
DOInot available

Abstract

fetched live from OpenAlex

In two longitudinal experiments, conducted both in the field and lab, we investigated the recollection of mixed emotions. Results demonstrated that the intensity of mixed emotions is generally underestimated at the time of recall—an effect that increases over time and does not occur to the same degree with unipolar emotions. Of note, the decline in memory of mixed emotions is distinct from the pattern found for memory of negative emotions, implying that the recall bias is diagnostic of the complexity of mixed emotions rather than of any association with negative affect. Finally, the memory decay effect was driven by the felt conflict aroused by the experience of mixed emotions. Imagine you are at Disneyland about to board the SpaceMountain ride. As you climb into your rocket, you feel joy and apprehension—a mixed feeling that persists even after the ride is over. You grip the safety bar, at once thrilled (the music is pumping, the lights are pulsing) and frightened (a semirational fear: people have been thrown from their rockets before). You leave the Space Mountain ride dizzy

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.782

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 head0.120
GPT teacher head0.295
Teacher spread0.174 · 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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