Smart Cities and Sustainable Urban Development in Morocco
Bibliographic record
Abstract
In a rapidly changing socio-economic context, urban planning faces several challenges.In fact, population growth, the accentuation of urban issues and the massive use of mobile communication technologies have presented the smart city as a relevant and innovative solution to these various contemporary challenges.At this stage, the opportunities mobilized by Big Data and communication technologies have reiterated the attention on the notion of smart cities.However, how can contemporary urban life be planned in order to determine the conditions for success and the trajectory of a smart city in Morocco?By crossing the reality of urban planning, the state of Moroccan cities with the different trajectories to be taken to support the emergence of smart cities in Morocco, this work seeks to explore the likely interactions between smart planning and the process of implementing a smart city.In addition, it also attempts to retrace the state of urban planning in Morocco.In this paper we will provide a series of concrete recommendations, ready to rectify any widespread deficiencies rooted in the current urban planning framework.Finally, we aim to propose some measures to be taken to ensure the redress of the excesses of the current planning system.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".