A Case Study of Non-Violent Property Crime Victimisation in a South African Urban Residential Neighbourhood: Exploring the Excessive Use of Force and Destruction Caused by Burglars to Gain Entry to Victims’ Properties
Bibliographic record
Abstract
Commentators frequently report on the high prevalence of violent crime in South Africa and often label the country as one of the most violent in the world, with a subculture of violence and criminality. This paper focuses on a different perspective, reporting on the excessive use of force and destruction caused by offenders in South Africa to gain entry to victims’ properties in the execution of non-violent property crimes, in a particular residential burglary. Literature on property crimes has been considering the aggravating circumstances of violent property crimes. However, the use of excessive force and destruction caused by burglars to gain access to victims’ properties in the execution of residential burglary remains relatively untested in the literature. In this light, the purpose of this study is to describe the unprecedented levels of force used and destruction caused by burglars to gain access to victims’ properties during residential burglary victimisation in an urban residential neighbourhood in Johannesburg, South Africa. A qualitative research approach is followed. A case study design was used to select an urban residential neighbourhood in Johannesburg as a case study. A data set of (n = 1 431) crimes were purposively selected by means of non-probability sampling. Qualitative and quantitative content analysis was used to analyse the data. This paper offers valuable insight into the forceful and destructive conduct of burglars in the selected neighbourhood and contributes to the body of knowledge by providing an improved understanding of target hardening as a preventive measure against residential burglary victimisation as well as on methods of entry used by burglars in incidents of residential burglary. The results of reported non-violent property crime victimisation incidences by this community’s neighbourhood watch scheme suggest that residential burglars in the selected neighbourhood are uncharacteristically forceful and ravage in their actions since they frequently revert to extreme use of force and destruction, disproportionate to the crime perpetrated. It is concluded that this radical degree of force used and destruction caused by residential burglars to gain entry to victims’ properties in the execution of non-violent property crimes is not typically associated with residential burglary as compared to countries internationally.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".