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Record W4367856450 · doi:10.5206/ijoh.2022.2.15207

The Extent of Homelessness in the Middle East and North Africa Region: A Scoping Review

2023· review· en· W4367856450 on OpenAlexaffvenue
Fawziah Rabiah-Mohammed, Abe Oudshoorn

Bibliographic record

VenueInternational Journal on Homelessness · 2023
Typereview
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWestern University
Fundersnot available
KeywordsDeclarationMiddle EastPolitical scienceScope (computer science)Meaning (existential)Gender studiesEconomic growthSociologyCriminologyPsychology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.871
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.334
GPT teacher head0.461
Teacher spread0.127 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2023
Admission routes2
Has abstractyes

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