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Record W2134786834 · doi:10.1037/a0021140

For God (or) country: The hydraulic relation between government instability and belief in religious sources of control.

2010· article· en· W2134786834 on OpenAlexaff
Aaron C. Kay, Steven Shepherd, Craig W. Blatz, Sook Ning Chua, Adam D. Galinsky

Bibliographic record

VenueJournal of Personality and Social Psychology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsMcGill UniversityMacEwan UniversityUniversity of Waterloo
Fundersnot available
KeywordsModerationMediationModerated mediationSocial psychologyFaithPsychologyGovernment (linguistics)Sociocultural evolutionControl (management)Perspective (graphical)Environmental ethicsPositive economicsSociologyEpistemologyLawPolitical scienceEconomics

Abstract

fetched live from OpenAlex

It has been recently proposed that people can flexibly rely on sources of control that are both internal and external to the self to satisfy the need to believe that their world is under control (i.e., that events do not unfold randomly or haphazardly). Consistent with this, past research demonstrates that, when personal control is threatened, people defend external systems of control, such as God and government. This theoretical perspective also suggests that belief in God and support for governmental systems, although seemingly disparate, will exhibit a hydraulic relationship with one another. Using both experimental and longitudinal designs in Eastern and Western cultures, the authors demonstrate that experimental manipulations or naturally occurring events (e.g., electoral instability) that lower faith in one of these external systems (e.g., the government) lead to subsequent increases in faith in the other (e.g., God). In addition, mediation and moderation analyses suggest that specific concerns with order and structure underlie these hydraulic effects. Implications for the psychological, sociocultural, and sociopolitical underpinnings of religious faith, as well as system justification theory, 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 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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.033
GPT teacher head0.358
Teacher spread0.325 · 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

Citations206
Published2010
Admission routes1
Has abstractyes

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