Bibliographic record
Abstract
The Rorschach inkblot test is the most commonly used projective measure in both clinical and forensic settings, and Exner's Comprehensive System (CS) is the most commonly used approach to Rorschach administration and scoring. However, recent studies of both adults and children have cast doubt on the representativeness of the CS norms. The analyses by Wood, Nezworski, Garb, and Lilienfeld provide compelling evidence that the CS adult norms are seriously flawed and are likely to result in frequent false positive identifications of psychopathology. We discuss the crucial need for appropriate norms in clinical assessment and examine the quality of the CS norms vis-a-vis those of other commonly used tests. We conclude that the concerns raised about the CS adult norms are sufficient to require the development of new norms for the CS. In the meantime, given the doubt that has been cast on the CS norms, it is crucial that the developers of the CS immediately move to provide ethically informed, scientifically based guidance to Rorschach users on how best to interpret adult Rorschach protocols.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.252 | 0.467 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".