Use of nonparametric statistical tests in defining the number of periods to include in an intertemporal DEA analysis
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Bibliographic record
Abstract
Abstract In any type of intertemporal efficiency analyses either locally or globally, units in different periods are compared against each other, and therefore it is assumed that no frontier shift exists within the periods of study. This assumption extends in window analysis to each window. In almost all studies in the past, the number of periods included in an intertemporal data envelopment analysis or the width of a window in a window analysis is determined without validating this assumption analytically. This is a problem which has not been fully addressed in the literature. This paper presents a new approach using nonparametric statistical tests to examine a frontier shift and determine the number of periods to include in an intertemporal analysis. The case of sawmills in Vancouver, Canada is used to demonstrate how to apply this new approach.
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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 | 0.015 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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