Do the Redundant and Locally Dependent Items of the LS/CMI Contribute in Any Meaningful Way to Its Reliability and Its Potential to Predict Criminal Recidivism?
Bibliographic record
Abstract
This article studies the effects of local dependence within the items of the first section of the LS/CMI on its reliability. Analysis were done to identify the dependent items namely through their correlations before and after Rasch modeling. Seven items were thus discarded, deemed dependent and redundant, and Cronbach's alpha was calculated with all 43 items and then with the 36 items deemed independent. Test information and predictive validity were also compared. Removing the seven redundant items did not seem to have major effects on the reliability of the LS/CMI or the psychometric information it provided, and no tangible effects were observed on its predictive validity. The reliability of an instrument should be assessed with items that contribute each in its own way. However, it is hazardous to report the reliability of an instrument known to be multidimensional with means meant to be used with unidimensional instruments.
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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 | 0.043 | 0.185 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".