Number-Right, Item-Response, and Finite-State Scoring: Robustness with Respect to Lack of Equally Classifiable Options and Item Option Independence
Bibliographic record
Abstract
The robustness of number-right; one-, two-, and three-parameter item-response; finite-state; and partial-credit scoring was examined with respect to the violation of the equally classifiable options and option independence made in finite-state scoring. All other assumptions underlying the use of these scoring models were met for each of four sub-tests that varied in terms of the violations. Analysis of the responses of 1,232 high school seniors on the subtests revealed that the number-right and one-, two-, and three-parameter scoring methods were equally sensitive to the presence of best answers (lack of option independence) and that the number-right and one- and two-parameter methods were equally sensitive to the presence of absurd option and stem-option connections (unequal classification of options) and pairs of similar or opposite options (lack of option independence, unequal classification of options). The three-parameter model and the finite-state scoring models were adversely sensitive to the presence of testwiseness.
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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 | 0.306 | 0.641 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".