A timely piece that resonates with the South African experience: Commentary on Stockwell <i>et al</i>.
Bibliographic record
Abstract
The authors correctly conclude that the burden from alcohol in Canada is substantially greater than it is from COVID-19, and thus, alcohol should be given more attention. However, they fail to mention that in some countries, with the rise in COVID-19-related hospital admissions, competition can occur between COVID-19 and trauma patients for scarce hospital resources. In South Africa, this has led to the temporary banning of alcohol sales at two periods during the lockdown. Stockwell et al. highlight the fact that alcohol is deemed an 'essential service' in many countries and point to the reasons why this might have occurred, and that industry appears to be taking advantage of lockdown conditions to expand their reach in ways that might continue after the lockdown. The alcohol industry in South Africa has also used the points given by Stockwell et al. as to why governments might be reluctant to restrict alcohol at this time in pushing back against imposition of alcohol control measures, and furthermore referred to the effect of the sales ban on jobs in the alcohol and related industries and policy inconsistencies in dealing with different industries. Finally, the commentary expands on the measures presented on how governments should use the opportunity provided by the COVID-19 crisis to push for further alcohol control measures to be implemented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".