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Record W2166008727 · doi:10.1177/0265407512464483

A prototype analysis of relational boredom

2012· article· en· W2166008727 on OpenAlexafffund
Cheryl Harasymchuk, Beverley Fehr

Bibliographic record

VenueJournal of Social and Personal Relationships · 2012
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsUniversity of WinnipegCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBoredomConceptualizationConstruct (python library)PsychologyNothingSocial psychologyCognitive psychologyComputer scienceEpistemologyArtificial intelligence

Abstract

fetched live from OpenAlex

Boredom has been described as a major obstacle to maintaining lasting love (Aron & Aron (1986). However, empirical research on this important challenge to relationship maintenance has been hampered by the lack of an agreed-upon definition of the construct. We tested the hypothesis that relational boredom is amenable to a prototype conceptualization. In study 1, participants provided prototypicality ratings for the features of relational boredom. Features such as “lack of interest in partner” and “no longer exciting” were considered prototypical of the construct, whereas features such as “nothing in common” and “too similar” were considered nonprototypical. We confirmed this prototype structure in the remaining studies. In study 2, when information that a couple was experiencing boredom was given, participants were more likely to infer that prototypical, than nonprototypical, features characterized the relationship. In study 3, the prototypical features were verified more quickly than the nonprototypical features in a reaction time task. In study 4, when a relationship was described in terms of prototypical, rather than nonprototypical, features of boredom, participants inferred greater boredom in the relationship. Moreover, these inferences were drawn more strongly for boredom than another negative relational state, namely conflict. Implications of these findings for theorizing and research on relational boredom are discussed.

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)0.001
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 score0.123
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.158
GPT teacher head0.323
Teacher spread0.166 · 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

Citations37
Published2012
Admission routes2
Has abstractyes

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