Testing the National Alcohol Policy Score Card (NAPSC) to assess progress in implementing a comprehensive policy response to reduce the harmful use of alcohol in South Africa
Bibliographic record
Abstract
Parry, C. (2013). Testing the National Alcohol Policy Score Card (NAPSC) to assess progress in implementing a comprehensive policy response to reduce the harmful use of alcohol in South Africa. The International Journal Of Alcohol And Drug Research, 3(3), 202 – 209. doi:http://dx.doi.org/10.7895/ijadr.v3i3.98Aims: To complement recent alcohol policy initiatives of WHO, a study was designed to test the feasibility of a simple instrument to assess the state of alcohol policy development and implementation in a developing country.Design: A cross-sectional survey.Setting: Data were collected via a web-survey.Participants: 52 experts across various sectors were approached.Measures: Study participants were asked to complete a 13-item web survey that draws on the target areas for national action identified in the World Health Organization (WHO) Global Strategy to Reduce the Harmful Use of Alcohol (2010). The state of policy development and implementation was assessed for 2011 and then retrospectively to 2006. Participants were also asked to comment on the ease of completing the survey.Findings: Based on the responses from 37 experts, improvements were noted in alcohol policy development and implementation in all areas over time, with particular movement in developing a national alcohol strategy; increasing leadership, awareness and commitment; drink-driving; and health services’ response. The total (average) score of 35% in 2011, while up by 11 percentage points, indicates that much work remains to be done, particularly to restrict the marketing of alcoholic beverages, address informal alcohol, increase community action to address harmful alcohol use, and increase financial resources.Conclusions: Participants found the web-survey easy to use. The overall findings and the way they are presented could be used to promote discussions around the development and implementation of national alcohol strategies and how they change over time, and even to compare the situations in different countries. Refinement of the instrument continues.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".