MétaCan
Menu
Back to cohort
Record W3121900038 · doi:10.1177/0963721417704394

Self-Control as Value-Based Choice

2017· article· en· W3121900038 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.

Bibliographic record

VenueCurrent Directions in Psychological Science · 2017
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Toronto
FundersNational Cancer InstituteNational Institute on Drug AbuseNational Institute on Aging
KeywordsPsychologyValue (mathematics)Control (management)Cognitive psychologySocial psychologyStatisticsArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Self-control is often conceived as a battle between “hot” impulsive processes and “cold” deliberative ones. Heeding the angel on one shoulder leads to success; following the demon on the other leads to failure. Self-control feels like a duality. What if that sensation is misleading, and despite how they feel, self-control decisions are just like any other choice? We argue that self-control is a form of value-based choice wherein options are assigned a subjective value and a decision is made through a dynamic integration process. We articulate how a value-based choice model of self-control can capture its phenomenology and account for relevant behavioral and neuroscientific data. This conceptualization of self-control links divergent scientific approaches, allows for more robust and precise hypothesis testing, and suggests novel pathways to improve self-control.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.125
GPT teacher head0.529
Teacher spread0.404 · 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