Positioning the Value of Dietary Carbohydrate, Carbohydrate Quality, Glycemic Index, and GI Labelling to the Canadian Consumer for Improving Dietary Patterns
Bibliographic record
Abstract
The objectives of this qualitative study was to: (1) understand Canadian consumers' knowledge and perception of dietary carbohydrates, carbohydrate quality, and the glycemic index (GI); and (2) determine Canadian's receptiveness to GI labelling to assist with identifying and consuming foods of higher carbohydrate quality. Focus groups were recruited in Vancouver, Toronto, and Montreal and grouped according to body mass index (BMI) (NBW, normal body weight; PO, previously obese; and OW/OB, overweight/obese) and diagnosis with prediabetes and diabetes (PO (Vancouver) and OW/OB (Montreal and Toronto). Subjects in all groups linked excess consumption of carbohydrate with weight gain. PO and OW/OB groups were conflicted between perceived negative consequences and feelings of pleasure associated with carbohydrate consumption. Subjects were largely unfamiliar with the term 'carbohydrate quality', but were often associated with classifying carbohydrates as 'good' or 'bad'. The concept of the GI resonated well across groups after exposure to corresponding educational materials. However, NBW groups largely felt that the GI was irrelevant to their dietary choices as they did not have a history of diabetes. PO and OW/OB groups associated the GI with diabetes management. The concept of a GI labelling program to help facilitate healthier carbohydrate choices was well received across all groups, especially when the low GI was interpreted as giving permission to consume foods they enjoyed eating. Results suggest that the GI could be used as a consumer-facing labelling program in Canada and assist with de-stigmatizing carbohydrate foods by helping to facilitate the consumption of carbohydrate foods that align with healthy dietary patterns.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".