Understanding Organic Food Qualities in the Global South: An East African Perspective
Bibliographic record
Abstract
Quality is a major component of the process of food production, delivery and consumption because it plays an influential role in consumer acceptability of the food. It has been widely suggested that food quality consists of both tangible and intangible (e.g., aesthetic) components although much of the debate has been based in the global north with little focus on southern countries. This paper therefore aims at exploring the concept of quality and more specifically organic food quality in East Africa (Uganda, Kenya and Tanzania). We carry out an extensive review of the relevant literature on food quality from a variety of electronic databases while exploring the cross cutting issues that are intrinsically connected to it in a bid to better understand both its explicit and implicit components. The findings suggest that in addition to the product and process qualities prominent in the global north, organic food in East Africa possesses context specific qualities which appear to play a greater role in the understanding of food quality within rural farming households because they satisfy some of their most pressing needs. This implies that how quality is interpreted will always depend on the situation or circumstances under which the user is operating in whether at the microcosmic (individual) or macrocosmic (regional) level.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".