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Record W3037536140 · doi:10.1521/jscp.2020.39.4.274

To the Victors Go the Existential Spoils: The Mental-Health Benefits of Cultural Worldview Defense for People WHO Successfully Meet Cultural Standards and Valued Goals

2020· article· en· W3037536140 on OpenAlexaff
Candice Hubley, Joseph Hayes, Mary R. Harvey, Santina Musto

Bibliographic record

VenueJournal of Social and Clinical Psychology · 2020
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTerror management theoryMortality saliencePsychologyFeelingSalience (neuroscience)Mental healthDistressExistentialismSocial psychologyDeath anxietyAnxietyClinical psychologyPsychotherapistPsychiatryCognitive psychology

Abstract

fetched live from OpenAlex

Introduction: Research in support of terror management theory suggests that mortality concerns will activate symbolic defenses associated with cultural worldviews, and when these defenses are activated, mental health will benefit. However, no study to date has examined this process in full. We filled this gap, while testing the moderating effect of feeling successful vis-à-vis cultural value-standards. Method: In two studies, we hypothesized that participants who feel successful at meeting cultural standards would engage cultural worldview defense (WVD) following mortality salience (MS), and as a consequence of their defensiveness, would experience greater mental health. Results: In Study 1, MS increased pro-American WVD only among relatively wealthy participants, which in turn reduced death-thought accessibility. In Study 2, MS increased pro-American WVD only among participants primed with felt success (vs. failure), which in turn reduced anxiety and depression. Conclusions: Culture can relieve death-related distress and promote mental health to the extent that it provides feelings of success.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.107
GPT teacher head0.475
Teacher spread0.368 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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