School learner's perceptions of the factors that influence methamphetamine use in Manenberg
Bibliographic record
Abstract
The aim of this study was to explore school learners' perceptions of the factors that influence methamphetamine use in Manenberg.To meet this aim, three objectives were proposed namely, to explore school learners' knowledge and understandings of methamphetamine use; to explore school learners' perceptions of methamphetamine and its uses and; to explore school learners' perceptions of the factors that influence methamphetamine use.Methamphetamine use amongst adolescents has become an increasing concern internationally and globally, with Cape Town's level of methamphetamine users being substantially higher compared to other parts of South Africa.The study was thus important as it firstly, permitted the understanding of adolescents' knowledge of methamphetamine and its uses in a lower socioeconomic status community, secondly, permitted the understanding of adolescents perceptions of the contributing factors of meth use, and thirdly, by knowing and understanding their viewpoints, key focus areas were recommended for intervention and prevention programs in an attempt to decrease the high drug rate in South Africa.A qualitative methodology was adopted for the study and participants were purposefully sampled from the three high schools in Manenberg.Information was gathered through focus group discussions and analysed using thematic analysis.The study strictly adhered to the ethics stipulated by the University of the Western Cape.Findings indicate that learners generally had a broad amount of knowledge about methamphetamine and commonly expressed disgust for users.Learners also perceived peer substance use and pressure, parental substance use, and poverty to be the risk factors for methamphetamine use in Manenberg.'Decreasing' factors noted by the participants mainly focused on improving intervention strategies as a means to decrease methamphetamine use in the area.Recommendations for interventions and improvement of interventions for all the risk factors noted were then stipulated.grandmother for all their support and faith during this year.To my father for all his sacrifices to get me to this point; to my mother for all her faith and uplifting talks; to my grandmother for all her prayers and confidence in my abilities; and to my brother for all his assistance and belief.I have been blessed with a supportive and faith bounded family that deserves all the acknowledgement for my achievements.Next, I would like to thank my Supervisor and the research team for all their assistance and confidence in me.I really appreciate it and have learned in abundance.I would also like to acknowledge and thank all the schools who have participated in the study and all those community leaders that assisted as well.In particular a great thank you goes out to the teachers and principles of Manenberg high school, Phoenix high school and Silverstream high school and especially the learners who participated.The financial assistance of the National Research Foundation (NRF) towards this research is acknowledged.Opinions expressed and conclusions arrived at are those of the author and are not necessarily to be attributed to the NRF.A special thank you also goes out to Mrs. M. Bennett who assisted me in obtaining the scholarship.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".