Antiquated Canadian Aircraft Noise Guidance—Setting the grounds for encroachment and adverse community impacts
Bibliographic record
Abstract
A comprehensive research project at the University of Windsor entitled Prediction and Management of Aircraft Noise Annoyance Around Canadian Airports reviewed multiple components of Canada’s TP 1247 Land Use in the Vicinity of Aerodromes. Using noise, complaints and survey data from Toronto Pearson International Airport, researchers evaluated the Noise Exposure Forecast (NEF) system as a tool for aircraft noise annoyance prediction and management. The NEF metric and its correlation to annoyance was examined as well as applicability of the NEF 30 threshold for the onset of significant annoyance. Further, the guideline for expected community response to noise was tested. The research found that most components of the NEF system are antiquated and in need of revision. A lack of prompt action to update Canadian guidelines for aircraft noise is setting the grounds for conflicts between stakeholders with competing interests and increasing the risks for greater noise impacts on future communities.
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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 | 0.019 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".