Critical Analysis of Strategies Towards Creating an Adequate Level of Awareness on Cybercrime among the Youth in Gauteng Province
Bibliographic record
Abstract
This study aims to determine any measures taken by the South African Police Service (SAPS) to create awareness about cybercrime among the youth in the selected policing areas in the Gauteng province. A qualitative research method was applied using semi-structured interviews to find the views of participants, of measures if any, to create youths’ awareness in the area of cybercrime. A total of 37 participants comprised of 29 youths aged between 19 and 35 years, including an additional eight participants from the SAPS Crime Intelligence Unit who agreed to participate. Among these participants, there were 18 females and 19 males. The findings highlighted that there was a lack of awareness on the measures taken by the SAPS in educating the youth about the risks associated with cybercrime. The other challenges highlighted by the SAPS were a lack of capacity, resources, and training to increase the technical skills amongst the SAPS members to work effectively on cybercrime-related challenges, lack of collaboration among role players to respond adequately to cybercrime, and ineffective implementation of cybercrime policies, therefore, there was a lack of cybercrime-related campaigns. Based on the findings, five themes were explored in this study, including a lack of capacity, resources, and training to increase the technical skills amongst the SAPS members to work effectively on cybercrime-related challenges, lack of collaboration among role players to respond adequately to cybercrime and ineffective implementation of cybercrime policies. The recommendations are provided as a potential step towards tailoring education packages and awareness programs to ensure at-risk groups are equipped with actionable mechanisms to protect themselves against cybercrimes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".