Explaining the self‐regulatory role of affect in identity theory: The role of self‐compassion
Bibliographic record
Abstract
OBJECTIVES: According to Stets and Burke's Identity Theory, people experience negative affect when their behaviour deviates from their identity standards, which drives the regulation of identity-relevant behaviour. Guilt and shame represent unique forms of negative affect. Self-compassion may influence guilt and shame responses about identity-behaviour inconsistencies. Relative to exercise identity, we examined the associations between (1) guilt and shame, behavioural intentions, and perceptions of identity-behaviour re-alignment after an identity-inconsistent situation and (2) whether self-compassion moderates the relationship between these forms of negative affect and both behavioural intentions and identity-behaviour re-alignment. DESIGN: Prospective, online, quantitative. METHODS: = 10.8 years, 50.2% women) who engaged in less exercise in the past week than their identity standard were recruited from Prolific.com. At baseline, self-compassion, state and trait guilt and shame, and exercise intentions were measured. One week later, participants reported the extent to which their past week's exercise aligned with their identity standard (i.e., identity-consistent perceptions). RESULTS: Neither state shame nor guilt related to exercise intentions nor identity-consistent perceptions. Self-compassion moderated the relationship between state guilt and identity-consistent perceptions (b = 2.524, SE = .975, t = 2.588, p = .010); state guilt was related to identity-behaviour consistency when self-compassion was high, but not when it was low. No other moderations were significant. CONCLUSIONS: This study adds nuance to Identity Theory and its propositions about negative affect and self-regulation; self-compassion may create the conditions necessary for negative affect to drive identity-relevant behaviour as proposed by identity theory.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".