Planning for a neighborhood and city-scale green network system in Qatar: the case of MIA Park
Bibliographic record
Abstract
Abstract In the past decade, Doha has witnessed fast-urban growth, an increased population rate, and an over-reliance on the automobile as the main mode of urban transportation. These factors caused social and environmental problems related to (1) the loss of a compact urban pattern, (2) an increased level of air pollution (3) high traffic congestions and (4) increasing landscape fragmentation. In consideration of such concerns, The State of Qatar invested large funds into the urban landscape development of Doha, as envisioned by Qatar National Vision 2030. As a result, in the past five years various parks and/or green areas, such MIA Park, a major public green space located around the Museum of Islamic Art (MIA), were planned and developed within metropolitan Doha. The authors argue that this park is currently facing issues and challenges related to (1) accessibility to/from the neighboring districts, and (2) connectivity to/from the neighboring parks. Therefore, this research study aims at assessing the existing conditions of MIA Park, at considering the broader city context and, at recommending strategies for implementing MIA Park’s green network system. It approached the investigative challenge using a multi-pronged comprehensive methodology, that deployed focus groups, semi-structured interviews and a comprehensive network analysis based on graph theory. The findings, revealed through these hybrid research tactics, allowed the researchers to generate a framework to enhance accessibility and connectivity of MIA Park through a green network system, planned at inter-related neighborhood-scale and city-scale levels. While the research examines most notably a single case, it is advocated that the proposed framework represents not just an optional feature pertaining to the case in Doha, but a valuable reference for the sustainable master planning of future cities in the State of Qatar and across the GCC. The paper proffers numerous key contributions, including the critical exploration of manufactured landscapes in Doha Qatar and the delineation of broadly applicable environmental design strategies to improve the fabric and livability of cities.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".