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Record W4385497348 · doi:10.1080/17439760.2023.2239781

Unique cognitive and emotional profiles of interpersonal gratitude and spiritual gratitude

2023· article· en· W4385497348 on OpenAlexaff
Cindel White, Kathryn A. Johnson, Behnam Mirbozorgi

Bibliographic record

VenueThe Journal of Positive Psychology · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsYork University
FundersJohn Templeton Foundation
KeywordsGratitudePsychologyFeelingAdmirationSocial psychologyInterpersonal communicationScholarshipAttributionInterpersonal relationship

Abstract

fetched live from OpenAlex

Gratitude is a prototypical emotional response when life’s blessings come from the intentional goodwill of other people, but many also attribute good experiences to the intervention of God, gods, a Higher Power, or other benevolent spiritual forces. This study investigated the differences between how United States participants (N = 610) experience interpersonal gratitude and spiritual gratitude. Compared to interpersonal gratitude, spiritual gratitude experiences were less often attributed to human action, more often attributed to supernatural beings and circumstances beyond human control, and elicited significantly less feelings of gratitude, indebtedness, and admiration, but greater awe. Participants reported the highest feelings of gratitude when they also believed in a personal God with a benevolent mind. These findings demonstrate the importance of perceiving benevolent agency in evoking feelings of gratitude, whereas experiences that are attributed to more abstract, less personified, or less external entities elicit a different profile of positive emotional responses.

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)0.000
metaresearch head score (Gemma)0.003
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
Metaresearch0.0000.003
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 head0.052
GPT teacher head0.350
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

Citations2
Published2023
Admission routes1
Has abstractyes

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