Killing the sacred dairy cow? Consumer preferences for plant‐based milk alternatives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We examine the relationship between demand for plant‐based milk alternatives and dairy milk using data from a survey and a discrete choice experiment completed by 902 Canadians. Our survey results show that most individuals who drink milk alternatives also consume dairy milk, and preferences for milk alternatives vary across consumption contexts. Using our experimental data, we estimate consumer preferences via a mixed logit model. These preferences are then used to calculate a set of price elasticities and to predict market shares for dairy milk in counterfactual simulations that exclude select milk alternatives. Although the elasticity of dairy milk with respect to the price of milk alternatives is relatively low, we predict that between 57% and 83% of respondents who purchase milk alternatives would have purchased dairy milk if milk alternatives were not available, depending on the counterfactual. We also show that preferences for milk alternatives are linked to age and food values. Finally, we use our experiment to test the impact of additional information about the impact of dairy milk on animal welfare, the environment, and nutrition on preferences for milk alternatives. The treatment effects are generally statistically insignificant. [EconLit Citations: L66, Q18, D12]
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.
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) | 0.000 | 0.001 |
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 it