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Record W3033195101 · doi:10.32872/spb.2663

Beyond God and government: The role of personal control in supporting citizens’ well-being in the face of changing economy and rising inequality

2020· article· en· W3033195101 on OpenAlexaff
Thuy-vy Thi Nguyen, Jonathon McPhetres, Edward L. Deci

Bibliographic record

VenueSocial Psychological Bulletin · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsHappinessEconomic inequalityGovernment (linguistics)Personal incomeInequalityGross domestic productLife satisfactionControl (management)EconomicsSubjective well-beingDemographic economicsEconomic growthSocial psychologySociologyPsychologyManagement

Abstract

fetched live from OpenAlex

Based on previous theoretical models, the present research investigated three different psychological constructs (religious belief, trust in government, and the experience of personal control) as moderators of the link between country’s economic growth (i.e., Gross Domestic Product) and income inequality (i.e., Gini) on health, happiness, and life satisfaction. Using a large cross-national data set (N = 490,579), we found that personal control predicted health, happiness, and life satisfaction above and beyond reliance on God and trust in government. Religious belief predicted greater health and buffered the negative effect of income inequality on health only in wealthy economies, but yielded negative correlations with health in poor economies. The associations between personal control and trust in government with well-being outcomes were consistently positive across different levels of countries’ GDP and Gini. Further, personal control also served a compensatory function by buffering the negative effect of income inequality in wealthy economies.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.300
Teacher spread0.281 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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