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Record W2053932839 · doi:10.1037/pspp0000039

Why bother? Death, failure, and fatalistic withdrawal from life.

2015· article· en· W2053932839 on OpenAlexaff
Joseph Hayes, Cindy L. P. Ward, Ian McGregor

Bibliographic record

VenueJournal of Personality and Social Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsWilfrid Laurier UniversityYork University
Fundersnot available
KeywordsPsychologyPessimismMortality salienceFatalismLife satisfactionGratificationDepression (economics)Learned helplessnessDeath anxietyDevelopmental psychologySocial psychologyClinical psychologyPsychiatryAnxiety

Abstract

fetched live from OpenAlex

The current research examines the conditions under which death contemplation will reduce, rather than increase, goal directed activity. By employing a goal-regulation perspective on the problem of death, we hypothesized that death awareness precipitates withdrawal from the goal for continued life when life is experienced as dissatisfying and hope for the future appears bleak. In Study 1, participants with low life satisfaction who contemplated goal failure responded to mortality salience with reduced desire for continued life. Studies 2-4 examined general goal motivation. Consistent with the idea that withdrawal from life precipitates a general state of reduced goal motivation, parallel effects were observed on the willingness to delay gratification for future outcomes (Study 2), orientation toward the future (Study 3), and behavioral activation system (BAS) sensitivity (Study 4). Moreover, Study 3 showed that these effects were mediated by a generally pessimistic attitude toward life. Finally, Study 5 assessed felt uncertainty and state depression, revealing that withdrawal from life was associated with reduced uncertainty but increased depression. Discussion is focused on implications for theories of threat and defense, and applications for understanding depression and suicide.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.069
GPT teacher head0.363
Teacher spread0.295 · 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 designNot applicable
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

Citations57
Published2015
Admission routes1
Has abstractyes

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