Rethinking Slums: An Approach for Slums Development towards Sustainability
Bibliographic record
Abstract
Slums have become an unavoidable reality in many countries of the world, particularly the developing world. Although there are various slums upgrading models and approaches to address the urban poverty in developing countries, the number of slum dwellers has actually grown and the problem is expected to become worse. Other public policies have to eradicate slums and didn't take into account the resources and the potentials that slums offer. This refers to the need to change the procedures followed in the development processes. Along with the human-related problems associated with slums, slums cause serious impacts on the environment and natural resources. In this context, sustainable development is the main outlet to achieve a real boom of the developing world that consequently confirms the need to develop slums in an integrated manner. So, this paper adopts a concept of investing the positive aspects of the slums' community in conjunction with developing a thorough framework based on the three pillars of sustainability, economy, society, and environment. From this vein, the research is guided by a set of successful practices of many of developing countries through an approach grounded on the three pillars of sustainability. The objectives of this paper are; 1) shedding light on the positive human power of slum dwellers, 2) disseminating best practices on sustainable approaches, from which it can be developed and adapted to fit in the context of the urban slums of developing countries, and 3) providing a comprehensive framework for developing sustainable slums.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".