Conceptualizing and Measuring Self-Criticism as Both a Personality Trait and a Personality State
Bibliographic record
Abstract
Blatt's (2004 Blatt, S. J. (2004). Experiences of depression: Theoretical, clinical, and research perspectives. Washington, DC: American Psychological Association.[Crossref] , [Google Scholar], 2008 Blatt, S. J. (2008). Polarities of experience: Relatedness and self-definition in personality development, psychopathology, and the therapeutic process. Washington, DC: American Psychological Association.[Crossref] , [Google Scholar]) conceptualization of self-criticism is consistent with a state–trait model that postulates meaningful variation in self-criticism both between persons (traits) and within person (states). We tested the state–trait model in a 7-day diary study with 99 college student participants. Each evening they completed a 6-item measure of self-criticism, as well as measures of perceived social support, positive and negative affect, compassionate and self-image goals during interactions with others, and interpersonal behavior, including overt self-criticism and given social support. As predicted, self-criticism displayed both trait-like variance between persons and daily fluctuations around individuals' mean scores for the week; slightly more than half of the total variance was between persons (ICC = .56). Numerous associations at both the between-persons and within-person levels were found between self-criticism and the other variables, indicating that individuals' mean levels of self-criticism over the week, and level of self-criticism on a given day relative to their personal mean, were related to their cognitions, affect, interpersonal goals, and behavior. The results supported the construct validity of the daily self-criticism measure. Moreover, the findings were consistent with the state–trait model and with Blatt's theoretical analysis of self-critical personality.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".