Bibliographic record
Abstract
<JATS1:p>Climate crises, a global pandemic, farmer protests, diet-related diseases—all of these are telling us that the industrial food system threatens our health and the health of the planet and deepens systemic inequities, racism, and poverty. Using food as an entry to key issues—such as Indigenous-settler relations and anti-racism in the food movement—Earth to Tables Legacies: Multimedia Food Conversations across Generations and Culturestells the stories of food activists from the Americas—young and old, rural and urban, Indigenous and settler—who share a vision for food justice and food sovereignty, from earth to tables. This visually stunning, full-color multimedia book generates rich conversations about food sovereignty through eleven photo essays and links to ten videos. Commentaries on each essay broaden the conversations with the experiences and perspectives of eighteen scholars and activists—both Indigenous and settler—from Mexico, the United States, and Canada. Facilitator’s guides offer creative ways to engage students and activists in critical discussions about these issues with links to other resources—text-based and visual, print and online. Visit the Earth to Tables websitehere.</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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.007 |
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; both teacher heads agree on what is shown here.
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".