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Record W3014908549 · doi:10.1177/1948550619898971

Gratitude Increases the Motivation to Fulfill a Partner’s Sexual Needs

2020· article· en· W3014908549 on OpenAlexaff
Ashlyn Brady, Levi R. Baker, Amy Muise, Emily A. Impett

Bibliographic record

VenueSocial Psychological and Personality Science · 2020
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsGratitudePsychologyRomanceSocial psychologySexual behaviorSexual relationshipSexual attractionInterpersonal relationshipDevelopmental psychologyHuman sexualityPsychoanalysis

Abstract

fetched live from OpenAlex

Maintaining sexual satisfaction is a critical, yet challenging, aspect of most romantic relationships. Although prior research has established that sexual communal strength (SCS)—i.e., the extent to which people are motivated to be responsive to their partner’s sexual needs—benefits romantic relationships, research has yet to identify factors that promote SCS. We predicted that gratitude would increase SCS because gratitude motivates partners to maintain close relationships. These predictions were supported in three studies with cross-sectional, longitudinal, and experimental methods. Specifically, experiencing and receiving expressions of gratitude were associated with greater SCS. These studies are the first to investigate the benefits of gratitude in the sexual domain and identify factors that promote SCS. Together, these results have important implications for relationship and sexual satisfaction in romantic relationships.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.157
GPT teacher head0.455
Teacher spread0.298 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

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