THE MUSHROOMING OF ALCOHOL ESTABLISHMENTS: A CASE STUDY OF GREENWELL MATONGO, WINDHOEK, NAMIBIA
Bibliographic record
Abstract
This qualitative paper aimed at exploring the mushrooming of alcohol establishments in a residential area and potential effects on a community in Namibia. A case study design was applied to explore experiences from 18 participants through in-depth interviews. The purposive sampling method was used to draw participants from various sectors in the community such as self-employed and unemployed persons, shebeen owners, general community members (community councillor, a school teacher, and a police officer), people working at shebeens, and residents who have signed the shebeen consent letter. Data were analyzed employing the thematic data analysis method. The collected data were themed into five major themes, namely economic effects, environmental effects, increase in alcohol consumption, poor parenting and an increase in crime. The paper noted that there is a high density of alcohol outlets which is mostly associated with social, economic and environmental effects. The study concluded that too many alcohol establishments in one community increase the chances of social ills compared to a community where alcohol outlets are fewer. This study recommends policy on a stricter monitoring system of alcohol outlets, especially in low-income communities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".