Environmental imperatives and the engineering interface: how to make hard decisions
Bibliographic record
Abstract
Parks Canada has been engaged in upgrading the Trans-Canada Highway in Banff National Park since 1979. A severe wildlife/vehicle collision problem existed and was predicted to worsen unless mitigation measures were employed. Permission to twin the highway from two lanes to four lanes was granted in phases, subject to exceptional environmental protection measures. Forty-five kilometers of highway have been twinned with 2.4-m-high fences and 24 large crossing structures. Parks Canada now is planning a 33-km continuance of the highway twinning project, with a 12-km segment presently under construction. Innovative environmental protection measures, based on the successes of earlier initiatives, are being employed. The most obvious of these measures have been fences and wildlife crossing structures to safeguard the rich assembly of wildlife resident or transient in the Bow River Valley. Valued ecosystem components include 12 species of large, highly transient Rocky Mountain wildlife, all subject to habitat fragmentation and vehicle collision. The species include protected native fish, Harlequin ducks, and a rich biodiversity in a high profile World Heritage Site. Parks Canada has a legal duty to maintain or restore ecological integrity in such undertakings. Research, planning, and design have high visibility in the presence of a motivated public who vigorously express divisive viewpoints. This presentation will explain: • How new designs respond to scientific imperatives • Science and social lessons learned • How to manage the confrontation of rhetoric and reality • How the future looks different than the past
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 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 | 0.031 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.035 |
| Scholarly communication | 0.035 | 0.037 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.013 | 0.020 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".