Standard Methods and Criteria Considerations for Residential Noise Complaints
Bibliographic record
Abstract
Acoustic consultants receive many inquiries about noisy neighbours, particularly from occupants of multi-unit residential buildings. There are currently no standards or regulations that objectively define thresholds for what is considered an annoyance or unacceptable noise intrusion. The lack of standardization for measurements, metrics, and criteria leaves complainants with little to no recourse, even when taking legal action. The development of a standard procedure and criteria would be a significant undertaking, but would be invaluable to acoustic engineers, local municipalities, noise by-law enforcement officers, and the public at large. This paper reviews relevant literature, outlines the major components for consideration in the development of a standard procedure and criteria, and will put forth a recommended framework for a standard approach.
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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 | 0.359 | 0.537 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.017 | 0.009 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".