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Record W4293546654 · doi:10.3390/socsci11090387

Human-Centred Design in UK Asylum Social Protection

2022· article· en· W4293546654 on OpenAlexaff
Michelle James, Rachel Forrester‐Jones

Bibliographic record

VenueSocial Sciences · 2022
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsWestern University
FundersEconomic and Social Research CouncilCaraUK Research and Innovation
KeywordsSocial protectionHuman rightsRefugeeSocial policyScholarshipPolitical scienceEquity (law)Social inequalitySociologyPovertyContext (archaeology)Economic growthInequalityEconomicsLaw

Abstract

fetched live from OpenAlex

This paper considers United Kingdom welfare provision for asylum seekers in the context of social protection scholarship, policy discourse more commonly associated with international development. Social protection definitions are contested, ranging from those focused on state provision to wider interpretations reflecting debates on holistic wellbeing, human rights and self-actualisation. Most recently, the 2030 Agenda for Sustainable Development has called for social protection policies for all citizens to reduce inequality among and within countries. Though there is exigency to reduce the extreme inequality existing between countries, literature is lacking on how social protection can be used to critique inequality within more economically affluent nations. Commentaries on social protection also tend to focus on economic poverty, with less attention given to vulnerabilities such as marginalisation. Literature suggests that UK asylum welfare provision is based on deterrence, control and marginalisation. In response, and to encourage equity in how all countries’ public policy is assessed, this paper utilises an international social protection framework to critique UK asylum welfare provision. It concludes by advocating for transdisciplinary, human-centred and comprehensive social protection policy design, encouraging participation by a wider range of stakeholders and a holistic understanding of wellbeing to meet asylum seekers’ needs effectively and efficiently.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0140.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.263
GPT teacher head0.459
Teacher spread0.196 · 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 designObservational
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

Citations7
Published2022
Admission routes1
Has abstractyes

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