The Canadian demand for healthy and unhealthy food: a comparison of food elasticity estimates using several different functional forms.
Bibliographic record
Abstract
Cet étude cherche d'évaluer la demande Canadienne pour les aliments sains vs. les aliments malsains trié selon revenus, et d'analyser la sensibilité de la population aux changements de prix et de dépenses. L'analyse est une extension du travail de Pomboza et Mbaga (2007), en regroupant davantage les aliments dans les catégories sains et malsains, et en appuyant plusieurs formes fonctionnelles alternatives à l'étude "Food Expenditure Survey and the Survey of Household Spending" datant de 2001. De ces cinque modèles, AIDS était celui qui est le mieux-adapté.Afin de diminuer l'occurrence des problèmes de spécification, cinq méthodes ont été considérées pour cette analyse. La courbe Engel, le modèle Rotterdam, le "Almost Ideal Demand System" (AIDS), l'approximation linéarisée du "Almost Ideal Demand System" (LAIDS), et la forme quadratique du "Almost Ideal Demand System" (QUAIDS) ont tous été considérés en termes de 1) les critères de la théorique en économie 2) la gamme des élasticités, et 3) la justesse de l'application du modèle.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".