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Record W3198577384 · doi:10.1123/jsep.2020-0342

Adjusting Identities When Times Change: The Role of Self-Compassion

2021· article· en· W3198577384 on OpenAlexaff
Sasha M. Kullman, Brittany Semenchuk, Benjamin J. I. Schellenberg, Laura Ceccarelli, Shaelyn M. Strachan

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPsychologyShameRuminationAbandonment (legal)Identity (music)Social psychologySelf-compassionDevelopmental psychologyFeelingClinical psychologyMindfulnessCognition

Abstract

fetched live from OpenAlex

Adjusting identity standards may be preferable to relentless pursuit or abandonment of an identity when facing an identity-challenging life transition. Self-compassion (SC) can help people adjust to challenges. The authors examined whether SC was associated with identity adjustment, exercise, and the moderating effect of identity-behavior discrepancy in 279 women exercisers who reported reduced exercise in motherhood. Participants completed the Self-Compassion Scale and reported the extent of and reflected on their identity discrepant behavior (reduced exercise). Reactions to discrepancy (acceptance, shame, guilt, and rumination), correlates of identity adjustment (subjective well-being, autonomous motivation, controlled motivation, and role conflict), and exercise behavior were assessed. SC associated positively with acceptance, correlates of successful identity adjustment, and exercise behavior. SC associated negatively with shame, rumination, and correlates of unsuccessful adjustment. SC may help exercise-identifying women who exercise less after becoming mothers adaptively cope with this identity challenge and continue exercising.

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)0.000
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 score0.408
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0090.000

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 head0.029
GPT teacher head0.325
Teacher spread0.295 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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