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Record W3097117532 · doi:10.1111/jopy.12604

Self‐control in daily life: Prevalence and effectiveness of diverse self‐control strategies

2020· article· en· W3097117532 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Personality · 2020
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of TorontoCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyDistractionSelf-controlControl (management)Experience sampling methodSocial psychologyDevelopmental psychologyCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: What strategies do people use to resist desires in their day-to-day life? How effective are these strategies? Do people use different strategies for different desires? This study addresses these questions using experience sampling to examine strategy use in daily life. METHOD: = 20.4, 63% female) reported on their use of six specific strategies (situation modification, distraction, reminding self of goals, promise to give in later, reminder of why it is bad, willpower) to resist desires (4,462 desires reported over a week). RESULTS: Participants reported using at least one strategy 89% of the time, and more than one strategy 25% of the time. Goal reminders and promises to give in later were more likely to be used for stronger desires. People also preferred different strategies for different types of desires (e.g., eating vs. leisure vs. work, etc.). CONCLUSION: In contrast to recent theoretical predictions, we find that many strategies, including inhibition, are similarly effective and that using multiple strategies is especially effective.

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.

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 score0.006
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.371
Teacher spread0.325 · 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