The Operating Efficiency of Vocational and Senior High Schools in Xindian District of New Taipei City: Three Envelopment Models in DEA
Bibliographic record
Abstract
<p class="1main-text">The purpose of this study is to apply a standard DEA model, cross-efficiency model and category variables DEA in evaluating operational efficiency for vocational and senior high schools in Xindan area, new Taipei city. The procedures this paper. Firstly, we do not consider neither different properties nor peer group for senior high or vocational school to evaluate their operational efficiencies by standard DEA model. Secondly, we apply DEA cross-efficiency (DEA-CE) model to perform self and peer-evaluation for the operational efficiency of the related different schools. Thirdly, we consider peer group and classify two groups in view of different properties to assess their performance by categorical variable DEA (CVDEA). Finally, by comparisons of the three performance results, the categorical variable model can better estimate operational efficiency for these vocational and senior high schools in the District of New Taipei City than that those of other two models.</p>
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".