Bibliographic record
Abstract
The intersection of food and immigration in North America, from the macroscale of national policy to the microscale of immigrants' lived, daily foodways. This volume considers the intersection of food and immigration at both the macroscale of national policy and the microscale of immigrant foodways—the intimate, daily performances of identity, culture, and community through food. Taken together, the chapters—which range from an account of the militarization of the agricultural borderlands of Yuma, Arizona, to a case study of Food Policy Council in Vancouver, Canada—demonstrate not only that we cannot talk about immigration without talking about food but also that we cannot talk about food without talking about immigration. The book investigates these questions through the construct of the immigrant-food nexus, which encompasses the constantly shifting relationships of food systems, immigration policy, and immigrant foodways. The contributors, many of whom are members of the immigrant communities they study, write from a range of disciplines. Three guiding themes organize the chapters: borders—cultural, physical, and geopolitical; labor, connecting agribusiness and immigrant lived experience; and identity narratives and politics, from “local food” to “dietary acculturation.” The open access edition of this book was made possible by generous funding from Arcadia – a charitable fund of Lisbet Rausing and Peter Baldwin. Contributors Julian Agyeman, Alison Hope Alkon, FernandoJ. Bosco, Kimberley Curtis, Katherine Dentzman, Colin Dring, Sydney Giacalone, Sarah D. Huang, Maryam Khojasteh, Jillian Linton, Pascale Joassart-Marcelli, Samuel C. H. Mindes, Laura-Anne Minkoff-Zern, Christopher Neubert, Fabiola Ortiz Valdez, Victoria Ostenso, Catarina Passidomo, Mary Beth Schmid, Sea Sloat, Kat Vang, Hannah Wittman, Sarah Wood
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".