First world hunger revisited : food charity or the right to food?
Bibliographic record
Abstract
Foreword by Olivier De Schutter, UN Special Rapporteur on the Right to Food (2008-2014) 1. Hunger in the Rich World: Food Aid and Right to Food Perspectives Graham Riches and Tiina Silvasti 2. Food Banks in Australia: Discouraging the Right to Food Sue Booth 3. A Right to Food Approach: Public Food Banks in Brazil Cecilia Rocha 4. Canada: Thirty Years of Food Charity and Public Policy Neglect Graham Riches and Valerie Tarasuk 5. Hunger and Food Aid in Estonia: a Local Authority and Family Obligation Juri Kore 6. Hunger in a Nordic Welfare State: Finland Tiina Silvasti and Jouko Karjalainen 7. Poverty Amid Growth: post-1997 Hong Kong Food Banks Kwong-leung Tang, Yu-hong Zhu and Yan-yan Chen 8. Privatising the Right to Food: Aotearoa/New Zealand Mike O'Brien 9. Between Markets and Masses: Food Assistance and Food Banks in South Africa Sheryl Hendriks and Angela McIntyre 10. Erosion of Rights, Uncritical Solidarity and Food Banks in Spain Karlos Perez de Armino 11. Food Banking in Turkey: Conservative Politics in a Neo-liberal State Mustafa Koc 12 Food Banks and Food Justice in 'Austerity Elizabeth Dowler 13. Food Assistance, Hunger and the End of Welfare in the USA Janet Poppendieck 14. Hunger and Food Charity in Rich Societies: What Hope for the Right to Food? Tiina Silvasti and Graham Riches References
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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".