Examining attitudes toward a proposed sugar-sweetened beverage tax among urban Indigenous adults: a qualitative study using a decolonizing lens
Bibliographic record
Abstract
BACKGROUND: Sugar-sweetened beverage taxation has been proposed as a public health policy to reduce consumption, and compared with other ethnic or racialized groups in Canada, off-reserve Indigenous populations consume sugar-sweetened beverages at higher frequencies and quantities. We sought to explore the acceptability and anticipated outcomes of a tax on sugar-sweetened beverages among Indigenous adults residing in an inner-city Canadian neighbourhood. METHODS: Using a community-based participatory research approach, we conducted semistructured interviews (November 2019-August 2020) with urban Indigenous adults using purposive sampling. Interviews were audio-recorded, transcribed verbatim and analyzed using theoretical thematic analysis. RESULTS: All 20 participants (10 female, 8 male and 2 two-spirit) consumed sugar-sweetened beverages on a regular, daily basis at the time of the interview or at some point in their lives. Most participants were opposed to and concerned about the prospect of sugar-sweetened beverage taxation owing to 3 interconnected themes: government is not trustworthy, taxes are ineffective and lead to inequitable outcomes, and Indigenous self-determination is critical. Participants discussed government's mismanagement of previous taxes and lack of prioritization of their community's specific needs. Most participants anticipated that Indigenous people in their community would continue to consume sugar-sweetened beverages, but that a tax would result in fewer resources for other necessities, including foods deemed healthy. INTERPRETATION: Low support for the tax among urban Indigenous people is characterized by distrust regarding the tax, policy-makers and its perceived effectiveness. Findings underscore the importance of self-determination in informing health policies that are equitable and nonstigmatizing.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".