EDUCATIONAL MIXED-USE BUILDING DESIGN AND ITS CONNECTIONS TO COMMUNITY ENGAGEMENT
Bibliographic record
Abstract
Education and extracurricular activities play a critical role in improving individuals’ personalities and building a healthy community. Lack of educational facilities, unapproachable educational resources and invalidity of space for physical activities is a great obstacle to strong community building. Pakistan has been going through several economic and political crises that are making it difficult for the government to provide educational resources and opportunities for sports and physical activities to its people. Therefore, this study aims to explore how mixed-use educational buildings can facilitate individuals in gaining knowledge and education easily along with other recreational activities. Mixed-use building design will enable individuals to socialise, community engagement, and fulfilling educational needs. This study utilized a survey by a questionnaire to understand the needs of individuals that can be fulfilled by a mixed-use space. The study participants were 100; mostly academics and school coaches took part in the study to evaluate the efficacy of mixed-use buildings. This study has a novel contribution to knowledge as it enhances the role of building design and architecture for mixed-use spaces in urban and rural areas of Pakistan to empower communities. The study results suggested a strong impact of mixed-use building design on community engagement.
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 | 0.002 | 0.003 |
| 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 | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".