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Record W2009280321 · doi:10.5964/ejop.v10i3.763

Humour Use Between Spouses and Positive and Negative Interpersonal Behaviours During Conflict

2014· article· en· W2009280321 on OpenAlexafffund
Lorne Campbell, Sarah Moroz

Bibliographic record

VenueEurope’s Journal of Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyDyadConflict resolutionSocial psychologyInterpersonal relationshipContext (archaeology)Interpersonal communicationConflict resolution strategyRomanceDevelopmental psychologyNegative emotion

Abstract

fetched live from OpenAlex

The present research investigated the relation between the use of positive, negative and instrumental humour in the context of romantic relationships and relational well-being as assessed by positive and negative patterns of conflict resolution behaviour. A sample of 116 heterosexual married couples completed scales of relational humour use as well as conflict resolution behaviour. Behaviour of couples while attempting to resolve a relationship based conflict was also coded by independent raters. Actor-Partner Interdependence Model (APIM) analyses showed patterns of actor and partner effects for each type of humour use. Specifically, positive humour use of both partners predicted more positive conflict resolution, whereas negative humour use of both partners predicted less positive conflict resolution. Additionally, instrumental humour use of both partners seemed to predict greater apathy during conflict resolution. Implications for considering couple humor use, assessed for both partners of the dyad, for understanding relational well-being 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.051
GPT teacher head0.368
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2014
Admission routes2
Has abstractyes

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Same venueEurope’s Journal of PsychologySame topicHumor Studies and ApplicationsFrench-language works237,207