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Record W2474421399

Noise Regulation at the Ontario Ministry of the Environment and Climate Change

2016· article· en· W2474421399 on OpenAlexaffvenueabout
T. F. Shevlin, Pierre Godbout

Bibliographic record

VenueCanadian acoustics · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsNoise (video)Christian ministryNoise controlAgency (philosophy)Government (linguistics)Environmental noiseEnvironmental planningNoise pollutionNoise regulationEngineeringBusinessEnvironmental resource managementPolitical scienceEnvironmental scienceComputer scienceNoise reductionSociology
DOInot available

Abstract

fetched live from OpenAlex

Provincial regulation of noise and vibration in Ontario is carried out by a small and diverse group of engineers working for the Ministry of the Environment and Climate Change, in the Environmental Approvals Branch. Their primary activity is the review of the noise aspects of Air and Noise ECAs (Environmental Compliance Approvals) for industrial installations. Several noise engineers are also dedicated to the REA (Renewable Energy Approval) process, primarily related to wind and solar farms. Additional duties include review of Environmental Assessments, investigation of noise complaints, testifying at hearings, and clarification of the provincial noise guidelines, especially as used by some municipalities. Although dealing with noise issues around land use approvals was transferred to the municipalities over 10 years ago, the noise engineers stepped up when the Ministry received a request from three levels of government to become involved in the Toronto Waterfront Revitalization effort and were successful in resolving a serious noise-based conflict between developers and a significant industry. Since the Ministry does not have a separate agency for formulating noise policy, such as exists for air contaminants, the noise engineers also play a large role in implementing policy changes. Recently the noise group, in coordination with the noise consulting community, the development sector, municipalities and private citizens, completed the first major revision of the MOECC’s noise guidelines in 20 years.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.002

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.

Opus teacher head0.013
GPT teacher head0.206
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes3
Has abstractyes

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