The Computerized Implicit Representation Test: Construct and incremental validity
Bibliographic record
Abstract
Discrepancies in mental representations between self-aspects and significant others are associated with depression, personality disorders, emotional reactivity, and interpersonal distress. The Computerized Implicit Representation Test (CIRT) is a novel measure developed to assess discrepancies in mental representations. Inpatient participants (N = 165) enrolled in a longitudinal study completed baseline CIRT ratings of similarity between self-aspects (actual-self, ideal-self, and ought-self) and between actual-self and significant others (mother, father, liked others, and disliked others). Based on the similarity ratings, multidimensional scaling was utilized to generate distances between key self- and other representations in three-dimensional space. Results of univariate linear regression analyses demonstrated that discrepancies (distances) between self-aspects, actual-self to others, and actual-self to mother were significantly associated with impulsive and self-destructive behaviors and/or lifetime anxiety disorders. Multivariate hierarchical linear regression models further indicated that three CIRT variables provided incremental validity above and beyond age, gender, and/or borderline personality disorder.
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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 | 0.001 | 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 | 0.001 |
| 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".