Maximal Accessibility Network Design in the Public Sector
Why this work is in the frame
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Bibliographic record
Abstract
This paper focuses on designing facility networks in the public sector so as to maximize the number of people benefiting from their services. We develop an analytical framework for the maximal accessibility network design problem that involves determining the optimal number, locations, and capacities of a network of public sector facilities. We assume that the time spent for receiving the service from a facility is a good proxy for its accessibility. We provide a generic model that incorporates both the congestion at the facilities and the customer-choice environment that underlies most of the services offered by the public sector. We devise an ɛ-optimal algorithm for the arising nonlinear integer program. The proposed algorithm performs well in tackling fairly large problem instances. Through a realistic example based on the hospital network of Toronto, we demonstrate the model’s capability in providing policy insights.
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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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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