A Quality Assessment Directory for Evaluating Multi-functional Public Spaces
Bibliographic record
Abstract
Abstract Public spaces facilitate opportunities for social interaction and promote social life. The social-spatial complexity of public spaces can be explored through the relationship between built forms and users’ daily social activities. The contemporary needs of users have retrofitted or replaced the controversial public spaces such as streets, depriving the prime function of sustaining and facilitating social life. Thus, any factors influencing users’ social/public life impact the quality of public spaces. Also, contextualization and definition of public spaces necessitate an evaluation of their quality. The lack of a quality assessment directory (QAD) for evaluating multi-functional public spaces motivated us to address it. To achieve the aim, this research has conducted a systematic literature review applying the content analysis to explore the principles and indicators influencing and enhancing social interactions in multi-functional public space design and then performed a normalization analysis to measure the weight of each indicator. The QAD constitutes five criteria (C1 – Inclusiveness, C2 – Desirable activities, C3 – Comfort, C4 – Safety, C5 – Pleasurability), and forty-two (42) embedded sub-criteria. The research found that Inclusiveness ( Wn C1 = 4.38) and Pleasurability ( Wn C2 = 3.88) have received the highest weights. Also, the research found that the sub-criteria ‘Physical/visual connection or openness to adjacent spaces’ ( Wn Sc.4.1 = 1.00), ‘Users of diverse ages’ and ‘Community gathering third places’ ( Wn = 0.750) have received the highest weights. Using such a QAD, urban professionals can quantify the effectiveness and efficiency of public spaces’ environmental and physical qualities in promoting social interactions and sociability.
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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 | 0.120 | 0.175 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.031 | 0.029 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".