Canadian Consumers’ Purchasing Behavior of Omega-3 Products
Bibliographic record
Abstract
The development of innovative functional food products is a major trend in today’s food industry. The growth of this industry is driven by increased consumer awareness of their own health deficiencies, increased understanding of the possible health benefits of functional foods, development in formulation technologies, a positive regulatory environment, and changing consumer demographics and lifestyles. While there has been a proliferation of omega-3 products such as milk, eggs, yogurt, and margarine in the Canadian food market, very little is known about consumers of these products. We use ACNielsen Homescan™ data combined with survey data to develop profiles of omega-3 consumers in Canada. The focus of the study is on consumers of four products: omega-3 milk, omega-3 yogurt, omega-3 margarine, and omega-3 eggs. We investigate whether there are significant differences between consumers and non-consumers of omega-3 products based on their age, income, education, and household composition. We also investigate whether a household’s use of Canada’s Food Guide and the Nutrition Facts table and consideration of the health benefits of food influences the decision to purchase omega-3 products. The results from the ordered probit model estimation show that the aging Canadian population is a major driver of omega-3 purchases. Also, the presence of children in the home increases the purchasing frequency of omega-3 yogurt and omega-3 margarine, and reading the Nutrition Facts table and considering the health benefits of food are important factors that affect omega-3 product purchases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".