The effect of various simultaneous sources of mechanical error in the estimators of correlation causing deflation in reliability: seeking the best options of correlation for deflation-corrected reliability
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Estimates of reliability by traditional estimators are deflated, because the item-total or item-score correlation ( Rit ) or principal component or factor loading ( λ i ) embedded in the estimators are seriously deflated. Different optional estimators of correlation that can replace Rit and λ i are compared in this article. Simulations show that estimators such as polychoric correlation ( R PC ), gamma ( G ), dimension-corrected G ( G 2 ), and attenuation-corrected Rit ( R AC ) and eta ( E AC ) reflect the true correlation without any loss of information with several sources of technical or mechanical error in the estimators of correlation (MEC) including extreme item difficulty and item variance, small number of categories in the item and in the score, and the varying distributions of the latent variable. To obtain deflation-corrected reliability, R PC , G , G 2 , R AC , and E AC are likely to be the best options closely followed by r-bireg or r-polyreg coefficient ( R REG ).
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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 | 0.032 | 0.184 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it