Crime and the design of residential property – exploring the theoretical background ‐ Part 1
Bibliographic record
Abstract
This paper provides a critical review of “Defensible Space” (Newman, 1973) and traces the development of Crime Prevention Through Environmental Design (CPTED) in America and Canada, and Secured By Design (SBD) initiatives in the UK. It is argued that various aspects of the theory have avoided consideration and require further investigation and research. It is opined that “defensible space” is the theoretical foundation to both CPTED and SBD and it is posited that a thorough re‐examination of Newman’s ideas will serve to deepen our understanding of the complex relationship between the built environment and crime. British (BS8220) and European (CEN TC/325) Standards relating to urban planning and environmental design and crime reduction are currently receiving detailed deliberation and are based firmly upon Newman’s ideas. The projected need for some 4.4 million new homes in Britain (DOE, 1995) by 2016 and Lord Roger’s call for improvements in urban design to reduce suburban migration from cities (DETR, 1999) reiterates the importance of the subject matter. This paper (the first of two) recognises that design per se does not represent the panacea for reducing criminogeneity, rather, that “defensible space” CPTED and SBD should be considered as crime prevention strategies, which can, in common with all other initiatives, contribute to tackling the problem of residential crime. In conclusion, it is argued that further research concerning how “defensible space” is perceived by various crucial stakeholders in society is the way forward in this regard. A second, forthcoming paper (PM, Vol. 19 No. 3) will present these research findings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".