Bibliographic record
Abstract
Abstract Between 1926 and 1933, the Empire Marketing Board used a myriad of advertisements, posters, exhibits, and films to promote the empire's food products to British homes. The publicity campaigns were intended to show that tea from India or fruit from Australia was not foreign, but also British. Whether the Board was successful in its bid to promote intra-imperial food consumption, indeed, whether those efforts were needed in the first place, was not clear. This article focuses on foods from Asia and America that were originally thought to be exotic in Europe, initially served as indicators of elite status, and their gradual dissemination downwards. It also examines the role of long-distance trade and modern technologies in the production and distribution of new agro-industrial foods across networks of imperial knowledge and commodity circulation. The article concludes by assessing the impact of global food corporations' domination in the contemporary era, which in many ways can be seen as the equivalent of the European and American empire of the past.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".