Bibliographic record
Abstract
This paper studies potato prices and consumption in the progress of economic development. Potato status tends to evolve from a luxury to a normal and, lastly, to an inferior good. In the developed world, where the potato thrived and became a food for the poor, prices of the inferior potato attract little interest due to general welfare, which further complicates discerning economic effects by computation. Contrarily, in many developing countries, due to supply constraints the potato is a relative expensive, non-staple, normal good, with little social significance. Whereas it is a common misconception that tastes in developing countries differ from advanced economies, low incomes, together with relatively high potato prices, present a real and obvious hindrance to wider potato use among the poor in the underdeveloped world. Local regressions on FAO data reveal empirical advantages favoring potato price system research in developing countries, more likely yielding predictable, statistically significant, unbiased results. Correct policies could increase potato importance in developing countries and stimulate sustainable and pro-poor growth where consumers receive affordable potatoes, while also producer incentives for greater productivity improve. Furthermore, potato-led research presents widening potential into also understanding general social structures of underdevelopment as similar factors explain both cross-border incomes and potato prices.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".