Influences of demographic characteristics, attitudes, and preferences of consumers on table egg consumption in British Columbia, Canada
Bibliographic record
Abstract
In addition to regular (white and brown) eggs, alternative types of table eggs (e.g., free-run, free-range, organic) are available in the Canadian market, and their market growth rate has been high during the last decade in British Columbia (BC). The objective of our research was to identify associations between consumers' attitudes, preferences, and demographic characteristics with their consumption of different types of table eggs. An online survey was conducted in June 2009 to gather information from adult BC residents. Sixty-eight percent of the 1,027 randomly selected subjects completed the survey. Our survey indicated that the consumption of cage-free specialty eggs (free-run, free-range, and organic) has strongly increased in BC to 32.9% free-range eggs, 11.93% organic eggs, and 7.6% free-run eggs in 2009 compared with a Print Measurement Bureau consumer survey that showed combined 8% consumption of cage-free specialty eggs in 2007. Results of our survey indicated that, compared with consumers of white regular eggs, consumers of free-range eggs came from smaller households and had a higher education level and income. These consumers indicated that factors of health, nutritional value, environmental issues, and animal welfare were important in egg type selection. Although most consumers rated the specialty eggs as having a higher nutritional value than white regular eggs, price became the most important deciding factor for those consumers who selected white regular eggs. Our findings indicate that increased consumption and increased differentiation exist in the table egg market and this in turn provides support for more research to increase the efficiency of cage-free egg production systems and for better consumer education.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".