Applying Context Sensitive Design to the Innovative Development of Major Highway Projects
Bibliographic record
Abstract
This paper explains how Context Sensitive Design (CSD) is being applied in the development of major Canadian projects requiring the construction and upgrading of arterial corridors. It continues the thesis of the author's paper to the 2002 TAC conference, which dealt with the emerging topic of CSD. This paper explores contemporary road design procedures that address the community context and follow the 1999 TAC Guidelines. These Guidelines allow for flexibility and the use of ranges of geometric parameters (domains) when supported by professional engineering judgment. They permit creativity and initiative as long as all decisions are documented with design heuristics and valid research. In this way, the context of communities, in terms of values and preferences, may be accommodated into road designs. The paper explains how project guidelines are being prepared for new road projects using the TAC Guidelines as their principal reference and explicitly addressing traffic safety. This is done by specifying geometric consistency and crash prediction modelling. These requirements place engineers at the forefront of the design task, mindful of their duties to society and to the likelihood of legal challenge. For the covering abstract of this conference see ITRD number E211395.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".