Bibliographic record
Abstract
Introduction Ethnography of Food Activism - Valeria Siniscalchi, Ecole Des Hautes Etudes En Sciences Sociales, France and Carole Counihan, Millersville University, USA Local Engagements Food Activism in Western Oregon - Joan E. Gross, Oregon State University, USA Engaging Latino Immigrants in Seattle Food Activism - Teresa M. Mares, University of Vermont, USA Resistance and Household Food Consumption in Santiago De Cuba - Hanna Garth, University of California at Los Angeles, USA Women, Gender and Food Activism in Italy - Carole Counihan, Millersville University, USA The Movement to Reinvigorate Local Food Culture in Kyoto, Japan - Greg De St. Maurice, University of Pittsburgh, USA National Actions French Biodynamic Viticulture: Militancy or Market Niche? - Marie-France Garcia Parpet, Institut De La Recherche Agronomique, France Sicilian 'Antimafia' Food Production Cooperatives - Theodoros Rakopoulos, Goldsmiths College London, UK The Canadian Wheat Board Struggle: Taking Freedom and Democracy to Market - Birgit Muller, Centre National De La Recherche Scientifique, France Brothers in Faith: Islamic Food Activism in Egypt - Nefissa Naguib, University of Bergen, Norway Transnational Networks Information, Transparency and Democracy in the Global Coffee Trade - Daniel Reichman, University of Rochester, USA Cultures of Corn and Anti-GM Activism in Mexico and Colombia - Elizabeth Fitting, Dalhousie University, Canada Peasants' Transnational Mobilization for Food Sovereignty in La Via Campesina - Delphine Thivet, Ecole Des Hautes Etudes En Sciences Sociales, France Oscillating Between Village and Globe: Articulating Food in Sri Lankan Activism - Wim Van Daele, Vrije Universiteit Brussel, Belgium Slow Food Activism Between Politics and Economy - Valeria Siniscalchi, Ecole Des Hautes Etudes En Sciences Sociales, France Bibliography Index
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".