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Record W2028707441 · doi:10.1080/02699930441000067

Hopelessness, stress, and perfectionism: The moderating effects of future thinking

2004· article· en· W2028707441 on OpenAlexaff
Rory C. O’Connor, Daryl B. O’Connor, Susan O’Connor, Jonathan Smallwood, Jeremy N. V. Miles

Bibliographic record

VenueCognition & Emotion · 2004
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPerfectionism (psychology)PsychologyConstruct (python library)Affect (linguistics)Stress (linguistics)Developmental psychologySocial psychologyClinical psychology

Abstract

fetched live from OpenAlex

It has been argued that a negative view of the future characterised by impaired positive future thinking is associated with increased hopelessness and suicide risk (e.g., MacLeod & Moore, 2000). Hence, the central focus of the two studies reported in this paper was to extend our knowledge of positive future thinking by investigating its relationship with established suicide risk factors: stress, perfectionism, and hopelessness. Study 1 demonstrates, for the first time, that positive future thinking moderates the relationship between stress and hopelessness. The findings of Study 2 replicated those found in Study 1 and they also supported the notion that perfectionism is best understood as a multidimensional construct and that its relationship with future thinking and hopelessness is not straightforward. The results are also discussed in terms of the relationship between the structure of affect and motivational systems.

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)0.004
metaresearch head score (Gemma)0.014
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.022
GPT teacher head0.311
Teacher spread0.289 · 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

Citations101
Published2004
Admission routes1
Has abstractyes

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