A national alcohol strategy for Chile: Rationale, development, content and status of implementation
Bibliographic record
Abstract
Giesbrecht, N., Sapag, J. C., Pemjean, A., Marquez, J., Khenti, A., Rehm, J., & Minoletti, A. (2013). A National Alcohol Strategy For Chile: Rationale, Development, Content and Status Of Implementation. International Journal of Alcohol and Drug Research, 2(2), 17-29. doi: 10.7895/ijadr.v2i2.128 (http://dx.doi.org/10.7895/ijadr.v2i2.128)Aim: This paper describes the rationale for the Chilean strategy on alcohol, how it was developed, its key recommendations, which of its dimensions have been implemented, and remaining challenges.Design: The paper is based on archival data, a literature review, and survey data from Chilean sources. It draws on presentations at two seminars in Santiago, and a background document commissioned by the Chilean Ministry of Health. Building on ongoing initiatives in Chile, it was informed by international research on the global and regional burden of disease from alcohol.Setting and Context:In 2008 the Ministry of Health, Government of Chile, embarked on developing a national alcohol strategy. The strategy’s rationale was informed by the high rate of alcohol-related trauma, including drinking and driving; the high rate of liver cirrhosis mortality and morbidity; the high rate of heavy drinking, including among youth and young adults; and gender differences.Measures: The main recommendations focused on several themes: pricing and taxation interventions, controlling physical availability, curtailing alcohol marketing, promoting server intervention, controlling drinking and driving, promoting community-based interventions, facilitating screening and brief interventions, and monitoring and tracking local and national developments on alcohol issues.Findings & Conclusions: Since 2008, there has been progress in several areas, including a National Strategy for brief interventions in primary care; a new law on legal blood alcohol content; proposals to increase taxes on spirits, introduce warning labels on beverage containers, and limit promotion of alcoholic beverages; and the integration of alcohol-related goals within the National Health Strategy 2011–2020. Nevertheless, challenges remain: the broad acceptance of drinking, including high-risk drinking; the importance and influence of the alcohol industry; and the need for an evidence-based inter-sector response.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.061 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".