Identifying Consumer Mindsets Related to Sugars Consumption in Canadian Adults
Bibliographic record
Abstract
Little is known about the attitudes and perceptions towards dietary sugars in Canadian adults. The objective of this study was to use rule-developing experimentation (RDE) to identify consumer mindsets related to dietary sugars in 18–50-year-old Canadians. Following an isomorphic permuted experimental design, participants (n = 269) each rated a unique set of 24 scenarios, each consisting of a distinct mixture of two to four messages about dietary sugars on a 5-point scale. A regression model was created for each respondent, identifying the value that each respondent attributed to each of the 16 messages. K-means clustering revealed three distinct mindset groups as follows: “Sugars Beliefs” (MS1), “Trend Analysts” (MS2), and “Health Seekers” (MS3). In conclusion, this study found that RDE is a useful methodological approach for evaluating how consumers think about dietary sugars and revealed mindset-specific messages that matter most to people who differ in their attitudes toward sugars.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".