Bibliographic record
Abstract
A review of the effects of ambient noise and reverberation on speech intelligibility in classrooms has been completed because of the long-standing lack of agreement on preferred acoustical criteria for unconstrained speech accessibility and communication in educational facilities. An overwhelming body of evidence has been collected to suggest that noise levels in particular are usually far in excess of any reasonable prescription for optimal conditions for understanding speech in classrooms. Quite surprisingly, poor classroom acoustics seem to be the prevailing condition for both normally-hearing and hearing-impaired students with reported A-weighted ambient noise levels 4-37 dB above values currently agreed upon to provide optimal understanding. Revision of currently proposed room acoustic performance criteria to ensure speech accessibility for all students indicates the need for a guideline weighted for age and one for more vulnerable groups. For teens (12-year-olds and older) and young adults having normal speech processing in noise, ambient noise levels not exceeding 40 dBA are suggested as acceptable, and reverberation times of about 0.5 s are concluded to be optimum. Younger students, having normal speech processing in noise for their age, would require noise levels ranging from 39 dBA for 10-11-year-olds to only 28.5 dBA for 6-7-year-olds. By contrast, groups suspected of delayed speech processing in noise may require levels as low as only 21.5 dBA at age 6-7. As one would expect, these more vulnerable students would include the hearing-impaired in the course of language development and non-native listeners.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".