Acoustical design strategies for open-plan workstations in green office buildings / Nurul Amira Abd Jalil
Bibliographic record
Abstract
Although it was well established that acoustic is a significant environmental stressor, it was often overlooked as an environmental element in office design. Being a quarter part of indoor environmental quality (IEQ), the introduction of green building movement was anticipated to bring improvement to all aspects of the IEQ including acoustics. Unfortunately, it did not seem to be the case. At present, office is the most prominent type of workplaces, and open-plan office is the most favourable type of offices. Acoustic quality in offices is essential as people spend most of their waking hours in the office. Good acoustic quality is achievable through design measures which consciously complement the acoustical environment. With regards to green office buildings in Malaysia, there is a gap in knowledge where this area of study has yet to be explored. Hence, before any proposal of acoustical design measures can be made, understanding of the underlying acoustic conditions in open-plan offices in green office buildings in Malaysia is essential. Therefore, the first two objectives of this study are to evaluate the level of acoustic quality in selected open-plan offices and identify the green design elements that influence the acoustic quality in those same open-plan offices. Understanding the basic acoustic and design conditions would assist in the investigation of suitable alternatives of design strategies and variables, and the formulation of design measures that need to be taken to achieve acoustically comfortable open-plan offices. This study was done using the combination of case study through site visits, observations, and field measurement; as well as computer modelling and acoustic simulation on experimental open-plan office layouts. Data findings revealed that internal design elements such as partitions between workstations and the layout arrangements play a significant role in achieving speech privacy in open-plan offices. However, design measures should not be limited to internal design strategies alone as attention towards other design factors such the room geometry and consideration of all relevant acoustic parameters could help in attaining acoustically comfortable open-plan offices.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".