Lounge Designs for the Budapest Office of a Multinational Company
Bibliographic record
Abstract
The research examines the function, design principles, and physical features of the lounges of open-plan offices and presents them through the lounge designs of the Budapest office building of a multinational company.The design developed from the questionnaire, which was evaluated by descriptive statistical analysis and used in the concept development process.The design sought answers to the problems arising from the open-plan office design, without any changes in the workspace though.The predesign study was not limited to the lounge spaces.The project also required an analysis of the overall office design to make out the deficiencies and needs.The new lounge design provides better working conditions even with the workspaces untouched.The design aims to create dedicated spaces where activities that reduce work performance can be relocated from the office space, thus reducing the load on the space.The research aims to develop a system of criteria and planning methodology -based on the results of a workspace questionnaire -that contributes to increasing employee comfort and work efficiency.The results of the questionnaire revealed that those working in the open-plan offices were primarily disturbed by the noisy work environment, congestion and lack of private space -these factors determined the function selection and design of the lounges.
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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 | 0.002 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".