Taxation and Sugar-Sweetened Beverages: Position of Dietitians of Canada
Bibliographic record
Abstract
Dietitians of Canada recommends that an excise tax of at least 10-20% be applied to sugar-sweetened beverages sold in Canada given the negative impact of these products on the health of the population and the viability of taxation as a means to reduce consumption. For the greatest impact, taxation measures should be combined with other policy interventions such as increasing access to healthy foods while decreasing access to unhealthy foods in schools, daycares, and recreation facilities; restrictions on the marketing of foods and beverages to children; and effective, long-term educational initiatives. This position is based on a comprehensive review of the literature. The Canadian population is experiencing high rates of obesity and excess weight. There is moderate quality evidence linking consumption of sugar-sweetened beverages to excess weight, obesity, and chronic disease onset in children and adults. Taxation of sugar-sweetened beverages holds substantiated potential for decreasing its consumption. Based on economic models and results from recent taxation efforts, an excise tax can lead to a decline in sugar-sweetened beverage purchase and consumption. Taxation of up to 20% can lead to a consumption decrease by approximately 10% in the first year of its implementation, with a postulated 2.6% decrease in weight per person on average. Revenue generated from taxation can be used to fund other obesity reduction initiatives. A number of influential national organizations support a tax on sugar-sweetened beverages.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".