Learners' views on access to drugs and deterrent value of present measures
Notice bibliographique
Résumé
This is an overview of a school safety project with the general aim of assisting relevant stakeholders to explore a problem-solving strategy for creating a safer schooling environment and one that is more conducive to a culture of teaching and learning. A more specific aim of this survey was to investigate how accessible drugs are to learners. Given the detrimental effects drugs have in society and using the research group's responses, one of the objectives was to determine the extent of current deterrent measures. The research sample comprised of 1988 learners from 35 primary and secondary schools in District 4 in the Pretoria school area. Most (56, 7%) of the respondents were female, compared with 43, 3 percent male. Learners younger than 17 years of age constituted 54 percent of the research group, while those aged 17 years and older represented 46 percent. Approximately 5 percent (5, 4%) of the respondents were from primary schools and 94, 6 percent from secondary schools. As regards population group, the majority of the respondents were black (41, 7%), followed by whites (37, 9%), Indians (10, 7%) and coloureds (9, 7%). The results revealed significant levels of difference between the respondents' perceptions and attitudes. The findings of this study indicated that 40 percent of the learners can buy drugs, such as dagga, within a few hours or less, while 30, 1 percent indicated that they can buy dagga within 30 minutes or less. Approximately one quarter (22, 1%) of learners indicated that they can buy hard drugs such as LSD, ecstasy, cocaine or heroin within a few hours. Furthermore, one quarter indicated that they know of learners at their school who sell illegal drugs, while 26, 7 percent have actually seen illegal drugs being sold at their schools or inside the school grounds. Another 42, 2 percent of the learners has also personally observed the sale of illegal drugs in their neighbourhood. Learners older than 16 years of age seem to be more familiar with the illegal drug market and its culture, and appear to have better access to drugs than their younger counterparts. Male respondents appear to be more knowledgeable than female learners about illegal drug activities. Coloured respondents are constantly over represented compared with the other population groups. The research findings on the extent to which drugs are accessible to learners obviously warrant a national follow-up research project.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».