Psychometric evaluation and proposed revision of the Mental Contamination Report
Bibliographic record
Abstract
Abstract Background/objectives: Substantial experimental research has explored mental contamination – feelings of internal pollution proposed to result from misinterpreting perceived violations. The Mental Contamination Report (MCR) was developed to measure in-the-moment experiences of mental contamination, and has been used in seminal experiments in this domain. However, the MCR has yet to be psychometrically evaluated. The aim of the current study was to evaluate the psychometric properties of the MCR, and if warranted, propose a revised version with improved research utility. Method: Data for this study were collected as part of a larger experiment examining the impact of moral self-violation on mental contamination. A sample of 150 undergraduate students completed the MCR, Vancouver Obsessional-Compulsive Inventory-Mental Contamination Subscale, and the Vancouver Obsessional-Compulsive Inventory. Results: The original Emotions Subscale of the MCR demonstrated excellent internal consistency ( ${\rm{\alpha }}$ =0.92) but contained emotions non-specific to mental contamination. We conducted an exploratory factor analysis (EFA) of the emotion items to identify which items load more heavily onto a mental contamination-specific factor. The EFA revealed a two-factor solution, with five items items loading strongly on the mental contamination-specific factor. For the 5-item mental contamination-specific Emotions Subscale, we found excellent internal consistency ( ${\rm{\alpha }}$ =0.90), strong known groups validity, F 2,147 =63.17, p <.001, η p 2 =.46, good convergent validity and mixed results for divergent validity. For the Behavioural Urges Subscale, we found overall mixed psychometric properties. Conclusions: Based on the results of the psychometric analysis, a revised version of the MCR is proposed.
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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 | 0.000 | 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".