Public giving to alleviate poverty: Surveying provider experiences of a novel scheme
Bibliographic record
Abstract
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.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".