A CRITICAL LEGAL PERSPECTIVE ON STATUTORY INTOXICATION – TIME TO SOBER UP?
Bibliographic record
Abstract
Intoxication has been a phenomenon since time immemorial. Alcoholic beverages play a central role in South African life and culture. Millions of rands are spent annually by government on “Arrive Alive” and “Zero Tolerance” campaigns in the fight against drunken driving. The liquor industry advertises aggressively, linking its products to positive cultural symbols and social needs. The use of alcohol and drugs is, however, also associated with personal, social and legal problems. The role of alcohol and drugs in South Africa’s escalating crime rate cannot be ignored. According to Jacobs, alcohol abuse is involved in a quarter of all admissions to general hospitals in the United States of America. This is precisely the reason that government put a total ban on the sale of alcoholic beverages when the Covid pandemic hit South Africa and hospitals were flooded with Covid patients. Alcohol abuse also plays a major role in the four most common causes of death of men aged 20 to 40: suicide, accidents, murder and cirrhosis of the liver. On 9 May 2022, the World Health Organization stated that the harmful use of alcohol is a causal factor in more than 200 disease and injury conditions. A million deaths annually result from harmful use of alcohol globally, which amounts to 5,3 per cent of all deaths worldwide. It was further stated that alcohol consumption causes death and disability relatively early in life; in mortalities of persons aged 20–39 years, approximately 13,5 per cent of total deaths are attributable to alcohol. It is, therefore, alarming that people who become voluntarily drunk, to this day, still stand a chance of being acquitted in South African courts if the evidence reveals that, at the time of the act, the accused happened to fall into the grey area between “slightly drunk” and “very drunk”. This legal position was once again confirmed in the case of S v Ramdass. The decision represents yet another instance where an accused who committed alleged crimes in a state of voluntary intoxication was acquitted on both counts. South Africa’s legal position on voluntary intoxication is clearly at odds with the global and national call for stricter regulations on the public’s excessive use of alcohol, which makes a consideration of the Ramdass judgment, and the policy behind it, deserving of closer analysis.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.061 |
| Scholarly communication | 0.014 | 0.025 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.026 | 0.032 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".