Social Aspects of Drug Addiction in Sri Lanka
Bibliographic record
Abstract
Social problems are rapidly increasing in modern societies due to various reasons. One of these is drug addiction, which has become a major issue in the contemporary world, as it is proving to be a serious social problem in both developing and underdeveloped countries. This review article that focuses on the social aspects of drug addiction in Sri Lanka is based on secondary data obtained from the published works of different authors; they provide details about the identity of drugs, drug addiction and the increasing number of addicts in Sri Lanka. Drug addiction has become an important issue due to its severe impact on public health, its tendency to encourage crime, cause diseases, poverty and destruction of family life in Sri Lanka. Heroin and cannabis (marijuana) are found to be the most commonly used drugs in Sri Lanka. Laws and policies designed to control drug abuse and regulations on drug addicts have not brought any major change or desired outcome in the Sri Lankan drug scene. Drug users in Sri Lanka get their supply of drugs from the underground drug market, which has its internal and external sources. Rehabilitation of drug addicts has become an urgent need in the country to protect its valuable citizens who are needed to build a sustainable nation that is free from drugs. Drug addiction is preventable and can be managed successfully if every citizen of the country gives his/ her full support and contribution.
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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 | 0.000 |
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".