Hedonic Analysis of Apple Attributes in Metropolitan Markets of Western Canada
Bibliographic record
Abstract
ABSTRACT Over the last decade, the level of competition in the Canadian apple industry has been affected by growing competitive pressures from increasing imports and the availability of other fresh fruits. In response to intensifying competition, the industry has introduced new apple varieties that are more desirable to consumers in terms of eating quality and improve growers’ profitability. British Columbia (BC) apple sales data were employed to examine the implicit value of apple attributes for apples sold in several metropolitan areas of western Canada (Vancouver, Calgary, Edmonton, Saskatoon, and Winnipeg). Linear hedonic price functions were estimated to determine price premiums paid for newer varieties, higher grades, and larger fruit size. In addition, the price effects of cold storage and seasonality were considered because of their association with apple quality. Wholesale prices were significantly influenced by apple fruits of newer varieties, grades, fruit sizes, and metropolitan area. Wholesalers also distinguished between Canadian and BC grades of different varieties. Wholesale prices varied across urban centers; they were relatively higher in Winnipeg and Saskatoon than in Vancouver [EconLit Classifications: Q110, Q130].
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".