Getting From Here To There - Mainstreaming Wildlife Crossing Structures Through Transdisciplinary Design Approaches To Collaborative Planning
Bibliographic record
Abstract
The effectiveness of wildlife crossing structures in mitigating the impacts of roads on species and ecosystems have been well-documented in scientific literature. Despite this, there are challenges associated with translating ecological knowledge into policy and practice. The study examines the planning process for wildlife crossing infrastructure using a case study in the context of the Greater Toronto and Hamilton Area and explored the potential of transdisciplinary collaboration and design thinking to enhance landscape connectivity. The study followed an iterative design research method incorporating knowledge from literature review, policy analysis and subject matter professional expertise derived through participant observation through work with the Toronto and Region Conservation Authority. This supported the development of a conceptual framework for actionable research to encourage the co-creation of practical knowledge and specific planning solutions. In addition, the study contributes valuable insight to the broader literature of sustainable landscape planning, road ecology and transportation planning.
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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 | 0.025 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".