The Extent of Homelessness in the Middle East and North Africa Region: A Scoping Review
Bibliographic record
Abstract
While the right to housing is a fundamental right per article 25 of the 1948 Universal Declaration of Human Rights, ‘homelessness’ is still generally a Western concept and not comprehensively recognized or addressed as a social issue in many countries, including many within the Middle East and North Africa. This paper looked at the literature on homelessness in the Middle East and North Africa (MENA) region to document the meaning and scope of homelessness within this region. After identifying and screening the relevant articles, 103 eligible articles were included in the final data synthesis stage. What we have learned from the review is organized in three categories: 1) conceptualizations of homelessness, 2) proposed responses to homelessness, and 3) research gaps. Studies addressing homelessness experienced by women, elderly, and family were underrepresented or did not exist. Homelessness among children dominates the literature in this review with 62% studies investigated the issue of homelessness in childhood. In a way, children are prioritized yet their adult relatives are often left invisible. Responding to the issue of homelessness on a global scale first involves having effective definitions that both properly enumerate and contextualize the issue. Without establishing a comprehensive definition of homelessness, efforts to address housing precarity can be ineffective.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".