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Record W4307228100 · doi:10.1177/09567976221110136

A Self-Controlled Mind Is Reflected by Stable Mental Processing

2022· article· en· W4307228100 on OpenAlexaffabout
Tobias Kleinert, Kyle Nash, Josh Leota, Thomas Koenig, Markus Heinrichs, Bastian Schiller

Bibliographic record

VenuePsychological Science · 2022
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologySelf-controlControl (management)ElectroencephalographyCognitive psychologyInhibitory controlDevelopmental psychologyCognitionNeuroscienceArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Self-control—the ability to inhibit inappropriate impulses—predicts economic, physical, and psychological well-being. However, recent findings demonstrate low correlations among self-control measures, raising the question of what self-control actually is. Here, we examined the idea that people high in self-control show more stable mental processing, characterized by processing steps that are fewer in number but longer lasting because of fewer interruptions by distracting impulses. To test this hypothesis, we relied on resting electroencephalography microstate analysis, a method that provides access to the stream of mental processing by assessing the sequential activation of neural networks. Across two samples (Study 1: N = 58 male adults from Germany; Study 2: N = 101 adults from Canada, 58 females), the temporal stability of resting networks (i.e., longer durations and fewer occurrences) was positively associated with self-reported self-control and a neural index of inhibitory control, and it was negatively associated with risk-taking behavior. These findings suggest that stable mental processing represents a core feature of a self-controlled mind.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0270.000

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 head0.093
GPT teacher head0.496
Teacher spread0.403 · 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.

Study designNot applicable
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

Citations19
Published2022
Admission routes2
Has abstractyes

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