MétaCan
Menu
Back to cohort
Record W2973733567 · doi:10.1126/sciadv.aax2615

Valuing time over money predicts happiness after a major life transition: A preregistered longitudinal study of graduating students

2019· article· en· W2973733567 on OpenAlexafffund
Ashley V. Whillans, Lucía Macchia, Elizabeth W. Dunn

Bibliographic record

VenueScience Advances · 2019
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of British Columbia
KeywordsHappinessTransition (genetics)PsychologyLongitudinal studySocial psychologyEconomicsBiologyMathematicsStatisticsGenetics

Abstract

fetched live from OpenAlex

How does prioritizing time or money shape major life decisions and subsequent well-being? In a preregistered longitudinal study of approximately 1000 graduating university students, respondents who valued time over money chose more intrinsically rewarding activities and were happier 1 year after graduation. These results remained significant controlling for baseline happiness and potential confounds, such as materialism and socioeconomic status, and when using alternative model specifications. These findings extend previous research by showing that the tendency to value time over money is predictive not only of daily consumer choices but also of major life decisions. In addition, this research uncovers a previously unidentified mechanism-the pursuit of intrinsically motivated activities-that underlies the previously observed association between valuing time and happiness. This work sheds new light on whether, when, and how valuing time shapes happiness.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.359
Teacher spread0.331 · 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 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

Citations21
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueScience AdvancesSame topicPsychological Well-being and Life SatisfactionFrench-language works237,207