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Record W4391288852 · doi:10.1177/01461672231223597

The SAFE Model: State Authenticity as a Function of Three Types of Fit

2024· article· en· W4391288852 on OpenAlexafffund
Audrey Aday, Yingchi Guo, Smriti Mehta, Serena Chen, William M. Hall, Friedrich M. Götz, Constantine Sedikides, Toni Schmader

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2024
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsBrock UniversityUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySocial psychologyVariation (astronomy)FluencyFunction (biology)CognitionState (computer science)Experience sampling methodCognitive psychologyMathematics educationMathematics

Abstract

fetched live from OpenAlex

The SAFE model asserts that state authenticity stems from three types of fit to the environment. Across two studies of university students, we validated instruments measuring self-concept, goal, and social fit as unique predictors of state authenticity. In Study 1 ( N = 969), relationships between fit and state authenticity were robust to controlling for conceptually similar and distinct variables. Using experience sampling methodology, Study 2 ( N = 269) provided evidence that fit and authenticity co-vary at the state (i.e., within-person) level, controlling for between-person effects. Momentary variation in each fit type predicted greater state authenticity, willingness to return to the situation, and state attachment to one’s university. Each fit type was also predicted by distinct contextual features (e.g., location, activity, company). Supporting a theorized link to cognitive fluency, situations eliciting self-concept fit elicited higher working memory capacity and lower emotional burnout. We discuss the implications of fit in educational contexts.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.999

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)0.0020.000

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 head0.109
GPT teacher head0.424
Teacher spread0.315 · 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 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

Citations24
Published2024
Admission routes2
Has abstractyes

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