Summary of outcomes of the cycling demonstration towns and \nCycling City and Towns Programmes
Bibliographic record
Abstract
The Cycling Demonstration Towns (CDT) programme ran from October 2005 to March 2011, and involved six medium-sized towns, with populations of between 65,000 and 245,000 people. The partly concurrent Cycling City and Towns (CCT) programme ran from July 2008 to March 2011. It involved one substantially larger city (Greater Bristol), one significantly smaller town (Leighton Linslade) and a further ten towns of medium size, with populations ranging from 75,000 to 240,000. \n \nOverall, we conclude that there is good evidence that the number of cycling trips has increased to varying degrees across the CDT and CCT programmes. Insufficient robust data is available to address the question of whether this increase is attributable to the investment programme, or simply reflects wider trends. Based on available evidence, we suggest that these programmes may have delivered greater uplift in cycling than would have happened without the investment, although we cannot say definitively that this is the case.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
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".