Current approaches to planning (with) sound
Bibliographic record
Abstract
While sound plays a critical role in our experience of the built environment, professionals feel ill-equipped to design and plan with sound in mind. Through a document analysis for 22 planning projects from Quebec, we aim to better understand how sound considerations are integrated into planning in practice. We identify and characterize the observed strategies and propose a typology of sound approaches in planning along two axes related to 1) the integration of the project into the pre-existing sound environment (from continuity to disruption) and 2) the nature and extent of sound considerations (from minimal to composite). This mapping revealed four main approaches to planning with sound, namely insufficient, sufficient, necessary, and extensive. The analysis further highlights a disconnect between planning and sound considerations, partly related to the abstract nature of planning considerations that exert an inherent but rarely acknowledged influence on sound. This disconnect is clearly visible at a tipping point between (flexible but vague) planning considerations and (concrete but technical) sound considerations when projects tend toward a more difficult integration into the pre-existing environment. We conclude with suggestions on how to move toward composite approaches to better integrate sound into 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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".