Examining correlates of body-related shame and guilt in a process model of self-conscious emotions
Bibliographic record
Abstract
This study tested the relationships in the process model of self-conscious emotions (Tracy & Robins, 2004). It was hypothesized that body-related shame occurs when individuals make stable, uncontrollable, and global attributions about the self and body-related guilt results from unstable, controllable, and specific attributions. Links were expected with identify-goal congruence and relevance, as well as attentional focus on the physical self. After reading hypothetical scenarios, males (n=105) and females (n=168; Mage=20.76±1.73) reported on physical self-worth, identity-goal relevance and congruence, attributions, and guilt and shame. Hierarchical regression analyses controlling for age, sex, and BMI were conducted. Relevance (s=.24), globality (s=.14) and universality (s=.20) were significant correlates of body-related shame (R2=.17). Controllability (s=.17), globality (s=.17), and universality (s=.14) were related to body-related guilt (R2=.13). Physical self-worth accounted for additional variance in body-related guilt (?R2=.03) and shame (?R2=.02). These results provide partial support for the process model, whereby inconsistencies with the model associations may indicate differences in attributional patterns for body-related contexts compared to generalized contexts. Since cognitive attributions play an important role in behaviour change, research is needed to examine the applicability of the process model of self-conscious emotions in context of the physical self.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".