Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<JATS1:p>Across the globe, people are challenging the agro-industrial food system and its exploitation of people and resources, reduction of local food varieties, and negative health consequences. In this collection leading international anthropologists explore food activism across the globe to show how people speak to, negotiate, or cope with power through food.</JATS1:p> <JATS1:p>Who are the actors of food activism and what forms of agency do they enact? What kinds of economy, exchanges, and market relations do they practice and promote? How are they organized and what are their scales of political action and power relations? Each chapter explores why and how people choose food as a means of forging social and economic justice, covering diverse forms of food activism from individual acts by consumers or producers to organized social groups or movements. The case studies embrace a wide geographical spectrum including Cuba, Sri Lanka, Egypt, Mexico, Italy, Canada, France, Colombia, Japan, and the USA.</JATS1:p> <JATS1:p>This is the first book to examine food activism in diverse local, national, and transnational settings, making it essential reading for students and scholars in anthropology and other fields interested in food, economy, politics and social change.</JATS1:p>
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it