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Record W4385548958 · doi:10.1007/s44155-023-00049-x

The role of civil society organizations in alcohol control during the COVID-19 pandemic across six countries in Africa

2023· article· en· W4385548958 on OpenAlexaff
Kashish Aneja, Aadielah Maker Diedericks, Sam Halabi, Katie Gottschalk, Kerry Waddell, Juan Tello

Bibliographic record

VenueDiscover Social Science and Health · 2023
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsMcMaster University
FundersWorld Health Organization
KeywordsCivil societyPandemicOutreachPsychological interventionPublic healthTanzaniaPolitical scienceEconomic growthEnvironmental healthCoronavirus disease 2019 (COVID-19)Development economicsSocioeconomicsMedicineSociologyPoliticsNursingEconomics

Abstract

fetched live from OpenAlex

Background: The differing global trends in alcohol consumption and policy measures implemented during the COVID-19 pandemic warrant a closer look at the actions taken by civil society organisations (CSOs) and community-led efforts to describe how they may influence and accelerate action for change in alcohol control measures. This paper analyses actions undertaken by CSOs at the national and local levels to safeguard communities and improve alcohol control policies during the COVID-19 pandemic in six African countries. Methods: A cross-sectional survey was distributed via email to CSOs involved in alcohol prevention, outreach and policy development in Kenya, Lesotho, Namibia, South Africa, Tanzania and Zimbabwe. Individuals (n = 19) working at CSOs responded to the questionnaire from February to March 2022. Questions related to the role of CSOs during the pandemic are analysed and synthesised in this paper. 19 CSOs respondents representing the six countries were included in the study. Results: Action areas led by CSOs during the COVID-19 pandemic included: (i) direct lobbying advocacy, (ii) conducting public awareness media campaigns and (iii) legal and regulatory interventions linked to the pandemic. Conclusions: Given the size of the challenges governments faced during the COVID-19 pandemic, the role of CSOs, during the ongoing pandemic and beyond, has become even more relevant to strengthen advocacy and public health interventions for alcohol control in Southern Africa. For this, CSOs should have a "seat at the table" when public health policies are designed, discussed and enforced.

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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.036
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.043
GPT teacher head0.372
Teacher spread0.329 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2023
Admission routes1
Has abstractyes

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