2006 Paratransit Survey: Paratransit Providers Strive to Balance Costs & Demand
Bibliographic record
Abstract
This third annual survey of paratransit providers shows that there is more growth from the private sector and that more public agencies are integrating demand-response with fixed-route service. Ridership is inching upward at 2.5 percent for 2005 and 3.7 for the first quarter of 2006 compared to the quarter a year earlier, attributed to the rise in the number of elderly riders as Baby Boomers age. Survey responses include total number of vehicles represented by agencies that took part. The largest fleet is more than 3,500 vehicles, and the smallest is three. Mean fleet size is 292, with median fleet being 86. The type of vehicles in the fleet and purchase plans are also reported. The survey draws on 36 operators from the U.S. and Canada, with respondents from 25 states, the District of Columbia and two Canadian provinces. Charts illustrate some findings and a list of the 10 largest public agencies and five notable private ones is included.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".