MétaCan
Menu
← Back to cohort
Record W4253624279 · doi:10.3148/cjdpr-2016-008

Taxation and Sugar-Sweetened Beverages: Position of Dietitians of Canada

2016· article· en· W4253624279 on OpenAlexvenueaboutno aff

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2016
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsExciseConsumption (sociology)ObesityEnvironmental healthBusinessTax revenueRevenueSugarPopulationRecreationMedicinePublic economicsFood scienceEconomicsPolitical science

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.091
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0120.006
Scholarly communication0.0070.003
Open science0.0030.003
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.032
GPT teacher head0.328
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations10
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Dietetic Practice and Research→Same topicObesity, Physical Activity, Diet→French-language works237,207→