Bibliographic record
Abstract
Aboca benefit corporation, 74-78 and biodiversity, 76-77 and SDGs, 77-78 Activism, 137 African pathway, 116-122 comparative country figures, 117 comparison of food and core inflation rates in South Africa compared to Ghana and Tanzania, 119 comparison of informal employment and unemployment, 118 African Union Development Agency (AUDA), 113-114 African Union inter-ministerial committee, 113-114 Agrarian citizenship, metabolic rifts and, 46-48 Agri-food capitalism, 11-12 Agri-food corporations, 61 Agri-food disruption and emerging transitions, responses and resistances to, 37-40 Agri-food production, 10 Agri-food sector, 72-74 Agri-food systems, 12-13, 130 public policy and multi-criteria nature of, 9-11 Agricultural Land Reserve (ALR), 50, 52-53 Agriculture, 153 Agriculture and Agro-Processing Master Plan (AAMP), 114 Agro-biodiversity, 76-77 Agro-ecological techniques, 163-164 Agroecological/organic farmers' markets, 135 Agroecology, 156 Alliance for Healthy and Adequate Food, 141 Alternative food networks, 89 Aspirational food sovereignty, 47 Austerity, 26 UN sustainable development goals, 71 Campina Grande markets, 95 Campina Grande street markets, 94 Canadian context, 5 Caruaru street markets, 95 Centro Agroecol ógico Rosario (CAR), 163-164 Centro de Producciones Agroecol ógicas Rosario (CEPAR), 157-159 Cheshire Cheese, 39 Cheshire Plain, 39 Chicken, case of, 32-34 Civil society as co-manager of public policies, 142-145 organisations, 133 in sustainable food systems, 5 Codes of conduct, 68-69 Colonial agriculture, 96 Committee on World Food Security (CFS), 143-144 Community, 114-115 Conservation of agro-biodiversity, 76-77 Conservatism, 30 Consumerism, food and politics of modern, 17-19 Consumers, 14 Continued financialised oligopolisation, 32-34 trends matter, 34 Conventional markets, 134-135 Cooperativa Ecol ógica Coolmeia, 132-133 Coronavirus Damage Prevention Plan, 135 Corporate and environmental regime, 24 Corporate food regime , responsibility and, 55 actors, 61 and drivers of pandemics, 59-60 and exacerbating effects, 60-61
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.779 | 0.816 |
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".