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Record W3165600456 · doi:10.1111/obr.13301

South Africa's Health Promotion Levy: Excise tax findings and equity potential

2021· review· en· W3165600456 on OpenAlex
Karen Hofman, Nicholas Stacey, Elizabeth C. Swart, Barry M. Popkin, Shu Wen Ng

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueObesity Reviews · 2021
Typereview
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentSouth African Medical Research CouncilMedical Research CouncilBloomberg PhilanthropiesNational Institutes of HealthInternational Development Research Centre
KeywordsExciseEquity (law)EconomicsBusinessPublic economicsMedicinePolitical scienceMacroeconomics

Abstract

fetched live from OpenAlex

In 2016, the South African government proposed a 20% sugar-sweetened beverage (SSB) tax. Protracted consultations with beverage manufacturers and the sugar industry followed. This resulted in a lower sugar-based beverage tax, the Health Promotion Levy (HPL), of approximately 10% coming into effect in April 2018. We provide a synthesis of findings until April 2021. Studies show that despite the lower rate, purchases of unhealthy SSBs and sugar intake consumption from SSBs fell. There were greater reductions in SSB purchases among both lower socioeconomic groups and in subpopulations with higher SSB consumption. These subpopulations bear larger burdens from obesity and related diseases, suggesting that this policy improves health equity. The current COVID-19 pandemic has impacted food and nutritional security. Increased pandemic mortality among people with obesity, diabetes, and hypertension highlight the importance of intersectoral public health disease-prevention policies like the HPL, which should be strengthened.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.763
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.004

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 head0.299
GPT teacher head0.526
Teacher spread0.227 · 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