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Record W3121211468 · doi:10.1080/16549716.2020.1856469

Study design: policy landscape analysis for sugar-sweetened beverage taxation in seven sub-Saharan African countries

2021· article· en· W3121211468 on OpenAlex
Anne Marie Thow, Agnes Erzse, Gershim Asiki, Charles Mulindabigwi Ruhara, Ahaibwe Gemma, Twalib Ngoma, Hans Justus Amukugo, Milka Wanjohi, Mulenga Mukanu, Lebogang Gaogane, Safura Abdool Karim, Karen Hofman

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

VenueGlobal Health Action · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsStakeholderContext (archaeology)DocumentationTanzaniaBusinessPolicy analysisPolitical scienceEconomic growthPublic economicsGeographyEconomicsPublic administrationEnvironmental planningPublic relations

Abstract

fetched live from OpenAlex

This paper reports on the design of a study to examine the policy landscape relevant to sugar-sweetened beverage taxation in seven sub-Saharan African countries. The study responds to the need for strong policy to address the rising burden of non-communicable diseases in the region. Sugar-sweetened beverage taxation has been widely recommended as a key component of a comprehensive policy approach to NCD prevention. However, it has proved a contentious policy intervention, with industry strongly opposing the introduction of such taxes. The aim was to identify opportunities to strengthen sugar-sweetened beverage taxation-related policy for the prevention of nutrition-related NCDs in a subset of Eastern and Southern African countries: Kenya, Tanzania, Botswana, Rwanda, Namibia, Zambia, Uganda. The study was conducted as a collaboration by researchers from nine institutions; including the seven study countries, South Africa, and Australia. The research protocol was collaboratively developed, drawing on theories of the policy process to examine the existing availability of evidence, policy context, and stakeholder interests and influence. This paper describes the development of a method for a policy landscape analysis to strengthen policies relevant to NCD prevention, and specifically sugar-sweetened beverage taxation. This takes the form of a prospective policy analysis, based on systematic documentary analysis supplemented by consultations with policy actors, that is feasible in low-resource settings. Data were collected from policy documents, government and industry reports, survey documentation, webpages, and academic literature. Consultations were conducted to verify the completeness of the policy-relevant data collection. We analysed the frames and beliefs regarding the policy 'problems', the existing policy context and understandings of sugar-sweetened beverage taxation as a potential policy intervention, and the political context across relevant sectors, including industry interests and influence in the policy process. This study design will provide insights to inform public health action to support sugar-sweetened beverage taxation in the region.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.372
Teacher spread0.311 · 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