Psychosocial and Demographic Factors That Compound Alcohol Abuse Amongst Youth: A Case Study of Musina High School
Bibliographic record
Abstract
The risk factors that compound alcohol abuse by young people have significant effects of individuals. The sole purpose of social work is to enhance the social functioning of clients and in most cases, clients have impairments as the result of high density of alcohol outlets, affordability of alcohol, which later give birth to psychosocial challenges. The aim of this study is to describe psychosocial and demographic factors compounding alcohol abuse amongst youth. The study employed quantitative approach and descriptive case study design. Data was collected at Musina High School and 96 learners were sampled using stratified sampling to complete the questionnaire. Data was analysed descriptively with the aid of Statistical Package for the Social Science. The study revealed that psychosocial and environmental factors compound to alcohol abuse amongst youth in Musina High School. The study concludes that the context determines the excessive use of alcohol abuse by youth. Young people especially those who reside in rural areas are exposed to high density of alcohol outlets and they are left without guardianship. Due to lack of guardian or parental involvement they end up indulging in excessive use of alcohol.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".