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Record W4417436454 · doi:10.35502/jcswb.483

Public giving to alleviate poverty: Surveying provider experiences of a novel scheme

2025· article· en· W4417436454 on OpenAlexvenueno aff
Matthew Jones, Ella Rabaiotti

Bibliographic record

VenueJournal of Community Safety and Well-Being · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersSwansea UniversityPublic Health Wales
KeywordsPovertyCashPerceptionScheme (mathematics)Food insecurityDeveloping country

Abstract

fetched live from OpenAlex

People experiencing poverty and homelessness are at increased risk of malnutrition and physical and mental illness, as well as involvement in crime. Food banks and other related schemes such as community fridges have become commonplace in the UK. However, as the prevalence of poverty increases, other novel methods may be needed to address individual and community well-being and safety. We carried out a survey to explore the attitudes, views and experiences of providers of an alternative giving scheme, developing across England and Wales, known as BillyChip. BillyChips are given to people experiencing homelessness as an alternative to cash and can be exchanged for food and drink at certain outlets. We found that the scheme is acceptable to providers and viewed positively. The experience of providing BillyChip tokens to people in need correlated with positive perceptions of the scheme in its role in alleviating poverty, whilst promoting individual safety. Providers suggested various additional items for redemption using the scheme. The learning from this study will be of interest to stakeholders involved in the development or adoption of BillyChip and other alternative giving schemes.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.078
GPT teacher head0.394
Teacher spread0.316 · 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 designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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