Acoustical Evaluation of High-School Technology-Education Shops
Bibliographic record
Abstract
This study investigated the acoustical conditions in high-school Technology-Education Shops (TES) and the conflict that may exist due to their use at the same time as classrooms for learning and as industrial workshops for fabrication. This was done by measuring relevant acoustical characteristics in twenty TES in British Columbia when unoccupied with building services operating, and in ten of them when occupied and in normal operation with shop equipment running. The results were compared to existing acceptability/design criteria for classrooms and industrial workshops, related to background-noise level, teacher noise exposure, reverberation time, speech-intelligibility index (SII) and sound-level reduction with distance doubling (DL 2 ), and pass/fail ratings were assigned. Noise levels and reverberation times in most unoccupied TES were higher than the acceptability/design criteria for core learning spaces. Teacher daily noise exposures in occupied TES were high and often exceeded regulatory limits. SII values often indicated ‘poor’ speech intelligibility for ‘normal’ and ‘raised’ vocal outputs, and ‘good’ speech intelligibility only for ‘loud’ and ‘shout’ vocal outputs. DL 2 values were unacceptable in most of the TES. Most TES received a failing grade with respect to most evaluation criteria. The results confirm the existence of an acoustical conflict; the acoustical conditions in the TES as industrial rooms are generally unsatisfactory for their use as classrooms. In general, the results suggest that TES provide poor acoustical conditions, overexposing teachers and students to noise, and are in need of effective sound-design and noise-control measures.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".