The Empirical Analysis of Terroir Versus Wine Pricing Relationships - The Case of the BC VQA Wines from the Okanagan and Similkameen Valleys
Bibliographic record
Abstract
The British Columbia (BC) wine industry is a puzzle because of the juxtaposition in classification of BC as a New World wine-producing region, with its winemaking and vineyard management approach that resembles the Old World wine-producing countries. Unlike the New World wine regions, the BC wine industry doesn’t build around a flagship grape variety, but around the uniqueness of terroir 2. The latest developments on the policy side, including wine industry plebiscite (spring/summer 2016) proposed the establishment of new appellations (4) and sub-appellations (16). Currently, wineries in BC produce wines from grapes that not always come from terroir associated with the location of their estates suggesting terroir heterogeneity. Knowing that specifics of terroir influence grapes quality and as a consequence wine quality, and being aware that quality of wine is correlated with its price an interesting research question arises: Does terroir matter for wine pricing in case of the Okanagan and Similkameen Valleys Vintners Quality Alliance (VQA) wines? In particular, this research investigates how various terroir elements influence wine price formation of the selected BC VQA wines. L'industrie du vin de la Colombie-Britannique (C.-B.) ressemble à un casse-tête dû à la juxtaposition de la classification de la C.-B. comme une région productrice de vin du Nouveau Monde, avec son approche de gestion des vignobles et de la vinification qui ressemble aux pays producteurs de vin du Vieux Monde. Contrairement aux régions vinicoles du Nouveau Monde, l'industrie du vin de la C.-B. ne se construit pas autour d'une variété de raisins vedettes, mais autour de l'unicité d'un terroir2. Les derniers développements du côté politique, incluant le plébiscite de l'industrie vinicole (printemps/été 2016), proposent l'établissement de nouvelles appellations (4) et sous-appellations (16). Actuellement, les entreprises vinicoles de la C.-B. produisent du vin à partir de raisins qui ne proviennent pas toujours du terroir associé avec la localisation de leurs domaines ce qui suggère une hétérogénéité du terroir. Sachant que les spécificités du terroir influencent la qualité des raisins et par conséquent la qualité du vin, et reconnaissant la corrélation entre la qualité du vin et son prix, une intéressante question de recherche se pose: le terroir importe-t-il pour déterminer le prix du vin dans le cas des vins Vintners Quality Alliance (VQA) des vallées de l'Okanagan et de Similkameen? Plus particulièrement, ce projet étudie comment différents éléments du terroir influencent la détermination du prix des vins BC VQA sélectionnés.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".