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Record W1855246521 · doi:10.25071/1920-7336.36480

Critical Challenges to Protecting Unaccompanied and Separated Foreign Children in the Western Cape: Lessons Learned at the University of Cape Town Refugee Rights Unit

2013· article· en· W1855246521 on OpenAlexvenueno aff
Tal Hanna Schreier

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeChild protectionDocumentationGovernment (linguistics)Unit (ring theory)Social protectionPolitical scienceWork (physics)Public administrationEconomic growthSocial workForeign policyLawPoliticsPsychologyEngineeringEconomics

Abstract

fetched live from OpenAlex

Despite South Africa having a relatively well developed legal and policy framework for securing the rights of children, there are a number of critical protection gaps that exist in terms of the implementation of these frameworks for unaccompanied or separated foreign children by magistrates, social workers and Department of Home Affairs’ officials in particular. This report focuses on the key challenges that the UCT Refugee Rights Unit has experienced in the protection of unaccompanied foreign children in the Western Cape province. In addition to setting out the legal and policy frameworks for dealing with foreign children in South Africa, the paper reviews some of the Unit’s cases and highlights various challenges in the course of undertakingthis work. The key protection gaps that are highlighted include difficulties with or lack of suitable entry by foreign unaccompanied or separated children into South Africa’s child care and protection system, the unclear interface between the refugee regime and the child protection regime, inability to access legal documentation, and the poor level of knowledge of the legal and protection frameworks by government and frontline service providers.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.969
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.316
Teacher spread0.272 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations6
Published2013
Admission routes1
Has abstractyes

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