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Record W6991123131

Exploring the acceptability of sugar-sweetened beverage taxes amongst residents of River Heights, Winnipeg: a critical discourse analysis

2022· dissertation· en· W6991123131 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2022
Typedissertation
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsnot available
Fundersnot available
KeywordsFocus groupCritical discourse analysisUnintended consequencesQualitative researchDiscourse analysisNeighbourhood (mathematics)Public healthWhite (mutation)
DOInot available

Abstract

fetched live from OpenAlex

Introduction: In response to public health focus on “obesity”, health organizations and governments have proposed a sugar-sweetened beverages (SSB) tax to reduce sugar intake, given their association with weight gain. However, “obesity” is already associated with social stigma, which intersects with other marginalized identities. Thus, a SSB tax may have unintended consequences because of the potential for exacerbating existing intersecting stigmas. Objectives: Our research objectives were: 1) To explore the discourses informing SSB taxation, and their underlying ideologies, amongst white residents of River Heights, Winnipeg, and 2) To determine the acceptability of SSB taxation to white residents of River Heights, Winnipeg. Methods: Qualitative interviews were performed with participants from River Heights, an upper-middle class neighbourhood in Winnipeg. Recruitment occurred based on: residence in River Heights, English-speaking, and being over 18 years old. We purposively recruited young adults, mothers, and regular consumers of SSB. The interviews were semi-structured, audio recorded and transcribed verbatim. Critical discourse analysis methods were used for analysis. Critical weight studies was used to inform analysis for objective 1, as well as theories of healthism and tax psychology for objective 2. Results: Eighteen participants were recruited; all were white, food secure, with high self-reported health, and spoke about (grand)parenting when discussing SSB. Fifteen participants were female. Objective 1: Discussion of SSB was framed by personal responsibility, which dictated the acceptability of SSB behaviours. Responsibilization of SSB behaviours were discussed in relation to weight and health, such that regular, or irresponsible, consumption, were largely discussed with negative emotions and judgement. Parental responsibility for SSB and juice intake of children was prominent throughout the interviews, and elicited judgement towards others and particularly among mothers, themselves. Objective 2: When discussing SSB taxation specifically, support for taxation mostly utilized healthism discourse, whereas criticism and concern was framed using concepts of fairness, and to a lesser extent, trust. Conclusions: SSB have complex social meanings, particularly in the context of taxation. The pervasiveness of moralisation with regard to SSB intake in participant discourse, and its priority over fairness concerns suggests that SSB taxation will have consequences for stigma and health equity.

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)0.012
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.597

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0130.012
Scholarly communication0.0070.003
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.081
GPT teacher head0.376
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 designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2022
Admission routes1
Has abstractyes

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