Analysis of the current development of community centers in Jeddah city
Bibliographic record
Abstract
Purpose The Kingdom of Saudi Arabia (KSA) has been experiencing extensive development in the fields of architecture and planning in recent decades, which has included developing community centers in neighborhoods. These community centers have significant impacts on the social, cultural, recreational and economic lives of the inhabitants. The study has looked into the concept of modeled and non-modeled community centers among 114 neighborhoods. Moreover, the study aims to suggest that decision-makers should make efficient decisions to uphold amenities through the centers at the neighborhood level after considering the evaluation techniques included in this paper to ensure a sustainable urbanization. Design/methodology/approach The authors collected both qualitative and quantitative information through structured and un-structured interviews in the city of Jeddah. Afterward, the authors evaluated the centers with a summarized grading point based on qualitative judgments. Note that the online questionnaire survey was prepared to distribute in approximately 100 neighborhoods. However, 71 neighborhoods took part in the survey, with a total number of 402 responses. Moreover, the authors made a subjective evaluation of the studied neighborhoods to understand the quality of services offered by the community centers. Findings The obtained results reveal that the community centers in the city of Jeddah are playing important roles for socialization, allowing younger people to interact in a positive way, providing services to the communities and supporting volunteer work in and around the neighborhoods. Consequently, the research paper emphasizes the future needs of these important social infrastructures as part of a neighborhood design tool in the context of Jeddah city, KSA. Originality/value This research attempts to document the need for community centers in the city of Jeddah. Consequently, the study evaluates 26 different community centers to understand whether the improvements are required for supporting community activities. Indeed, few research works have made an effort to study community centers’ role in urban life in a unique geographic context. Through this research project, the authors have highlighted the implications of community centers in urban life in the city of Jeddah.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".