Differential Performance on National Exams
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
The purpose of this study is to evaluate two methodological perspectives of test fairness using a national Secondary School Certificate (SSC) examinations. SSC is a suit of multi-subject national qualification tests at Grade 10 level in South Asian countries, such as Bangladesh, India, and Pakistan. Because it is a high-stakes test, the fairness of SSC tests is a major concern among public and educational policy planners. This study is a first attempt to investigate test fairness of the national SSC examination of Pakistan using two independent differential item functioning (DIF) and differential bundle functioning (DBF) procedures. The SSC was evaluated for possible gender bias using multiple-choice tests in three core subjects, namely, English, Mathematics, and Physics. The study was conducted in two phases using explanatory item response model (EIRM) and Simultaneous Item Bias Test (SIBTEST). In Phase 1, test items were studied for DIF, and items with severe DIF were flagged in each subject. In Phase 2, the item bundles were analyzed for DBF. Three items were detected with large DIF, one for each subject, and one item bundle was detected with a negligible DBF. Taken together, the results demonstrate that there is no major threat to the validity of the interpretation of examinees’ test scores on the SSC examination. The outcome from this study provided evidence for test fairness, which will enhance test development practices at the national examination authorities.
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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 | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.006 | 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 it