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Record W4401584784 · doi:10.1177/08854122241266816

Supporting the Living Laboratory: A Literature Review of Montreal Sound-Related Research

2024· review· en· W4401584784 on OpenAlexafffundabout
Edda Bild, Daniel Steele, Catherine Guastavino

Bibliographic record

VenueJournal of Planning Literature · 2024
Typereview
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
FundersMitacs
KeywordsSound (geography)Agency (philosophy)Noise controlPublic relationsSociologyPolitical scienceComputer scienceSocial scienceAcoustics

Abstract

fetched live from OpenAlex

Sound and noise play a critical role in the experience of urban environments. We review the literature on sound environments in Montreal and their effects on city users, including public sector reports from the City of Montreal and Montreal’s public health agency in addition to academic research, published between 2010 and 2020. 73 studies were analyzed according to scale, methodologies, methods, settings, sound sources covered, and domains of findings. This review summarizes the main findings at city level, paving the way for more integrated urban sound and noise policies tailored to local realities while staying informed of international best practices.

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)0.005
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.918
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0110.018
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.089
GPT teacher head0.538
Teacher spread0.449 · 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
GenreReview

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
Published2024
Admission routes3
Has abstractyes

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