MEAN SQUARED ERROR ESTIMATION FOR SMALL AREAS WHEN THE SMALL AREA VARIANCES ARE ESTIMATED
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Bibliographic record
Abstract
This paper suggests a generalization to Prasad and Rao’s estimator for the mean squared errors of small area estimators. This new approach uses the conditional mean squared error estimator of Rivest and Belmonte (2000) as an intermediate step in the derivation. It is used in this paper to incorporate, in the mean squared error estimator for a small area, uncertainty concerning the estimation of the small area variances 2 i . The impact of adding a term to Prasad-Rao mean squared error estimator for the estimation of 2 is investigated in a Monte Carlo experiment. An example concerned with the estimation of the under coverage of the Canadian census in sub-provincial ages-sex category is also presented.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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