Bibliographic record
Abstract
Introduction: The United Nations Office on Drugs and Crime (UNODC) in line with its mandates works with families and communities in various low-and-middle income countries settings in the light of the International Standards for Prevention of Drug Use (UNODC/WHO, 2018) and the International Standards for the Treatment of Drug Use Disorders (UNODC/WHO, 2020). Method: Initial monitoring and evaluation results of UNODC supported science-and family-based programs will be shared. Key Findings: Families and communities are key to promote emotional, physical and social development and the achievement of the Sustainable Development Goals. Feasibility and effectiveness of different family prevention and family treatment programs has been demonstrated across many countries. Discussions and Conclusions: Family factors and contexts in which families live can be both a risk a protective factor when it comes to the onset of drug use and the development of drug use disorders. Effective programs and interventions on various levels can enhance the supportive potential of families in the creation of societies more resilient to drugs and crime. There is a need for further monitoring and evaluation of interventions in different contexts. Implications for Practice or Policy: A key role in the mandates of UNODC is to provide technical assistance and thus translate science to practice in support of United Nations Member States on effective drug use disorder prevention, treatment and care. Implications for Translational Research: The work presented includes information from implementation studies on evidencebased interventions adapted to in low-and middle-income countries. Disclosure of Interest Statement: AB is a staff member of the United Nations. The author alone is responsible for the views expressed in this presentation
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".