Developing an Urban Health Planning Framework for Algiers: Assessing Vulnerability to COVID-19
Bibliographic record
Abstract
This study investigates the impacts of the COVID-19 pandemic on urban planning to develop an urban resilience strategy.The vulnerability assessment of Algiers to COVID-19 seeks to develop a correlation between the pandemics' global systemic impacts and Algiers' local urban potential.This research outlines the methodological approach of the Group Analysis Method (GAM), the multi-criteria decision analysis method (MCDA), and the qualitative analytical reading method (SFPO) -Successes, Failures, Potential, and Obstacles.These methods allowed us to build the Restricted Targeted Self-Audit (RTSA) and finally the planning framework.This study yields two distinct types of results: theoretical findings related to the expansion of the urban sustainability model and the empirical findings triggered by the issue of pandemic resilience.The results of this study aim to enhance residents' adaptation to major urban risks through proactive urban planning actions.This will help prevent a critical crisis for the city and its inhabitants in the event of a future pandemic.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".