Interrater Reliability of the Fitness Interview Test across 4 Professional Groups
Bibliographic record
Abstract
OBJECTIVE: This study investigated the interrater reliability of the Fitness Interview Test (FIT), revised edition, a semistructured interview that assesses fitness to stand trial. METHOD: Physicians, forensic psychologists, nurses, and graduate students in psychology were trained in the FIT, and they subsequently viewed 2 videotaped interviews of actual fitness assessments. Using the FIT, they rated the fitness of each defendant portrayed in the videotapes. RESULTS: For overall judgment of fitness, the average intraclass correlation based on the full samples of raters was found to be 0.98, and for most items on the FIT, intraclass correlations fell within the 0.80 s and 0.90 s. Reliability estimates were high across professional groups. CONCLUSIONS: Overall, this study provides further support for the psychometric properties of the FIT, as well as for the ability of various professionals to conduct reliable fitness assessments using the FIT.
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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 | 0.031 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".