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Record W2582460127 · doi:10.7939/r3sj0h

Time Perspective, Well-being, and Hope

2012· article· en· W2582460127 on OpenAlexaboutno aff
Jesse J.N. McElheran

Bibliographic record

VenueUniversity of Alberta Library · 2012
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)EpistemologyComputer sciencePhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

Time perspective (TP) represents a person's tendency to focus more on the past, present or future and has been shown to predict measures of individual well-being (Boniwell, et al., 2010). This study examined the relationship between one’s time perspective and measures of hedonic and eudaimonic well-being, specifically positive and negative affect, satisfaction with life, and self-actualization. Furthermore, this study explored hope across the different time perspectives. Two hundred and eighty eight Canadian adults were recruited via social media websites. Hierarchical cluster analysis was used to validate the Balanced Time Perspective construct and suggests that the Hedonism time profile is as adaptive as the Balanced Time Perspective. Correlational analysis was used to examine the association between hope and the five different time perspectives. Results indicate that the past positive time perspective is most predictive of high levels of hope. Results were discussed and integrated into current time perspective and hope research.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
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 head0.015
GPT teacher head0.260
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2012
Admission routes1
Has abstractyes

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