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Record W4410334497 · doi:10.1111/jasp.13101

Is Life Getting Better and Better or Worse and Worse for Oneself and Others? Investigating the Link Between Beliefs About Life Unfolding Over Time and Motivation for a Positive Future

2025· article· en· W4410334497 on OpenAlexafffund
Melissa Beaucage, Michael A. Busseri

Bibliographic record

VenueJournal of Applied Social Psychology · 2025
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyLink (geometry)Social psychology

Abstract

fetched live from OpenAlex

ABSTRACT We report two preregistered studies examining how individuals view life to be unfolding over time for themselves, people in their community, country, and all of humanity. We evaluated the link between such beliefs and “well‐doing,” that is, the motivation to engage in actions geared toward an improved future. In Study 1 ( N = 963; M age = 40.83 years; 48.2% female), individuals reported their beliefs about how life is unfolding over time for people in one of four target conditions: self, community, country, or all of humanity. In Study 2 ( N = 947; M age = 39.52; 51.4% female), individuals were randomly assigned to one of three narrative direction conditions (better, stable, worse) for one of the four target conditions. In Study 1, participants viewed life as getting better over time for the self, on average, but getting worse for the other targets. In both studies, perceiving life as improving (vs. worsening) was associated with stronger well‐doing intentions, particularly in the self condition in Study 1 and with respect to participants' general motivation in Study 2 regardless of target condition. Thus, viewing life as getting better and better (vs. worse and worse) over time may play an important role in motivating individuals to strive toward making life better, not only for oneself but also for people in one's community, country, and all of humanity.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.032
GPT teacher head0.352
Teacher spread0.320 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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