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Record W2747025132 · doi:10.1177/0276236617724070

Materialism, Temporal Orientation, and Well-Being

2017· article· en· W2747025132 on OpenAlexaff
David Watson

Bibliographic record

VenueImagination Cognition and Personality · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsMacEwan University
Fundersnot available
KeywordsFatalismMaterialismCultural materialism (cultural studies)Orientation (vector space)PsychologySocial psychologyEpistemologyPhilosophyMathematicsGeometry

Abstract

fetched live from OpenAlex

The research is an exploration of temporal orientation (past, present, and future) and materialism. Temporal orientation has been related to negative outcomes in the case of past orientation and both positive and negative outcomes with the present or future temporal focus. Given the well-established relationship between low-subjective well-being and materialism, it is hypothesized that materialism will be associated with past- and present-fatalistic temporal focus. Two studies were conducted using self-report with samples of 406 and 409 university students using measures of materialism, temporal orientation, and subjective well-being. The results indicated that materialism was correlated with past temporal orientation. Past-negative, rather than past-positive experiences were associated with materialism. Focus on present fatalism was also related to materialism. Past-negative and past temporal orientation was found to mediate the relationship between subjective well-being and materialism.

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)0.003
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.054
GPT teacher head0.415
Teacher spread0.361 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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