Quantifying Technical Efficiency of Paratransit Systems by Data Envelopment Analysis Method
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
This research evaluates efficiency levels of individual paratransit systems in Canada with the specific objective of identifying the most efficient agencies and the sources of their efficiency. Through identification of the most efficient systems along with the influencing factors, new service policies and management and operational strategies might be developed for improved resource utilization and quality of services. The research applies the data envelopment analysis methodology, which is a mathematical programming technique for determining the efficiency of individual systems as compared with their peers in multiple performance measures. Annual operating data from 2001 to 2003 as reported by the Canadian Urban Transit Association are used in this analysis. A bootstrap regression analysis is performed to identify the possible relationship between the efficiency of a paratransit system and measurable operating or managerial factors that affect the performance of paratransit systems. The regression analysis allows for the calculation of confidence intervals and bias for the efficiency scores.
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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 | 0.104 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.007 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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