Automatic Self Recriminations: Development and Validation of a Measure of Self-Condemnatory Internal Dialogue
Bibliographic record
Abstract
This article introduces a measure of self-condemnatory internal dialogue as an element of the relationship with the self: The Automatic Self-Recrimination Scale (ASRS). Using the construct validation approach to test construction, we describe the initial development of items and report on findings from a clinical and nonclinical sample showing the ASRS is best understood as a multidimensional measure of self-critical internal dialogue composed of one higher-order factor and four lower-order facets: Not Mattering, Self as Failure, Undeserving Self, and Loathsomeness. The overall scale and four subscales demonstrated acceptable internal consistency and test-retest reliability. Moreover, there was evidence of good convergent and incremental validity of the ASRS subscales with measures of perfectionism, self-criticism, and dysfunctional attitudes. Overall, the ASRS appears to be a reliable and valid measure of an automatic self-recriminatory internal dialogue.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".