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Record W1913419816 · doi:10.1111/spc3.12184

The System‐Justifying Function of Gratitude Norms

2015· article· en· W1913419816 on OpenAlexaff
Richard P. Eibach, Matthew O. Wilmot, Lisa K. Libby

Bibliographic record

VenueSocial and Personality Psychology Compass · 2015
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGratitudeSocial psychologyPsychologyFunction (biology)Interpersonal communicationContext (archaeology)Expression (computer science)Interpersonal relationshipReciprocity (cultural anthropology)IdeologyEpistemologyPolitical scienceLawComputer sciencePolitics

Abstract

fetched live from OpenAlex

Abstract We propose that gratitude norms function to motivate people to express system‐justifying beliefs and attitudes. When people feel grateful for the benefits they receive from sociopolitical institutions, they may feel compelled to express their appreciation by self‐censoring any grievances they may have about the functioning of their system. We review theory and research on the psychology of gratitude and integrate it with theory and research on the system‐justification motive. We illustrate how new insights into various effects in the literature on ideology and system justification might be gained by considering how the expression of system‐justifying opinions might function as an expression of gratitude toward one's system. We speculate that this system‐justifying function of gratitude is a consequence of social norms that overgeneralize the domain of gratitude from the context of interpersonal relations between peers to the context of relations with the larger, impersonal systems that govern people's lives.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.266
GPT teacher head0.432
Teacher spread0.167 · 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

Citations42
Published2015
Admission routes1
Has abstractyes

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