Report Active Quarter: Brackmills Industrial Estate 2022 – Active Travel and Physical Activity Infrastructure
Bibliographic record
Abstract
The University of Northampton conducted an audit of the footpaths and cycleways through Brackmills Industrial Estate, Northampton, using open-source data from the Census 2011, 2019 English Indices of Deprivation and OpenStreetMap (OSM) for desk-based mapping as well as a site visit to review existing street furniture that has been reported to influence walking and cycling levels. The report provides a detailed audit of the Industrial Estate, and the subsequent recommendations from this work are outlined below. Short-Term • Review the wayfinding in the Industrial Estate to cover minor gaps in the current provision and ensure clarity in route signage. • Update the information board maps to align with existing finger post signs and Brackmills BID branding. • Review vegetation maintenance schedule to reduce the encroachment of vegetation onto shared use paths and streetlights. • Review missing or broken streetlighting. • Targeted active travel support to employees who live within the 20-minute walking and cycling boundaries, e.g., eBike trials. Medium-Term • Review crossing points along the footpaths and cycleways to ensure they meet LTN 1/20 standard. • Work with employers to provide secure cycle parking, storage, and shower facilities. • Removal of chicanes and bollards that do not meet LTN 1/20 standard. Long-Term • Review the provision of bus shelters and seating across the Industrial Estate so employees can shelter during bad weather and pedestrians have places to rest if they are unable to walk for long uninterrupted periods. • Review all footpaths, cycleways, and shared use paths to determine upgrades needed to meet LTN 1/20 standard across the Industrial Estate.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.111 | 0.046 |
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".