MétaCan
Menu
Back to cohort
Record W3092898282 · doi:10.1177/0265407520966049

How can I thank you? Highlighting the benefactor’s responsiveness or costs when expressing gratitude

2020· article· en· W3092898282 on OpenAlexafffund
Yoobin Park, Mariko L. Visserman, Natalie M. Sisson, Bonnie M. Le, Jennifer E. Stellar, Emily A. Impett

Bibliographic record

VenueJournal of Social and Personal Relationships · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsYork UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGratitudeFeelingPsychologySocial psychologyAction (physics)

Abstract

fetched live from OpenAlex

Despite growing evidence that showing gratitude plays a powerful role in building social connections, little is known about how to best express gratitude to maximize its relational benefits. In this research, we examined how two key ways of expressing gratitude—conveying that the benefactor’s kind action met one’s needs (responsiveness-highlighting) and acknowledging how costly the action was (cost-highlighting)—impact benefactors’ reactions to the gratitude and feelings about their relationship. Using observer ratings of gratitude expressions during couples’ live interactions ( N = 111 couples), and benefactors’ self-reports across a 14-day experience sampling study ( N = 463 daily reports), we found that responsiveness-highlighting was associated with benefactors’ positive feelings about the gratitude expression and the relationship. In contrast, cost-highlighting had no such effect. These findings suggest that expressing gratitude in a way that highlights how responsive benefactors were may be critical to reaping the relational benefits of gratitude and have practical implications for improving couples’ well-being.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.518
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.136
GPT teacher head0.333
Teacher spread0.197 · 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

Citations20
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Social and Personal RelationshipsSame topicPsychological Well-being and Life SatisfactionFrench-language works237,207