Scale Validation via Quantifying Item Validity Using the <i> D <sub>m</sub> </i> Index
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While most validity indices are based on total test scores, this paper describes a method for quantifying the construct validity of items. The approach is based on the item selection technique originally described by Piazza in 1980. Unfortunately, Piazza's P2 index suffers from some substantial limitations. The Dm coefficient provides an alternative which can be used for item selection and provides a validity index for a set of items. The index is similar to that of traditional criterion-related validity indices. Criterion-related validity is used to demonstrate the accuracy of hypothesized relations of the measure with outcome variables of interest in research and practice. This method may be useful when the sample of items or persons is small, rendering more traditional approaches such as factor analysis or item response theory inappropriate. An example of how to use the technique is provided.
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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 | 0.021 | 0.101 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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