![Step 28: Identify risky facilities Step 28: Identify risky facilities](images/titles/steptitle_28-2.gif)
Facilities are environments with special functions (Step 15). Educational facilities involve teaching and study. Industrial facilities produce and process materials. Office facilities process information. Retail facilities involve sales and monetary transactions. Some facilities are frequent sites for crime and incivilities. These include taverns, parks, railway stations, payphone booths, convenience stores, and public housing projects. These facilities make a disproportionately large contribution to crime and disorder - they are "risky facilities."
But the term has also a more precise meaning. It refers to the fact that within each type of facility a few of them are especially risky. When we described the 80-20 rule in Step 18, we mentioned that 5 percent of the stores in Danvers, Massachusetts, accounted for 50 percent of the reported shopliftings (see the table provided by Christopher Bruce, crime analyst in the Danvers Police Department). Here are some other documented examples of risky facilities:
- Convenience stores. A national survey found that 6.5 percent of convenience stores experience 65 percent of all robberies.
- Gas Stations. Ten percent of Austin, Texas gas stations accounted for more than 50 percent of calls for driveoffs and drug crimes in 1998-1999.
- Banks. Four percent of U.K. banks have rates of robbery four to six times higher than other banks.
- Schools. Eight percent of Stockholm schools suffered 50 percent of the violent crimes reported in the 19931994 school year.
- Bus stops. Andrew Newton's recent doctoral dissertation reported that 9 percent of the shelters at bus stops in the British city of Liverpool experienced more than 40 percent of the vandalism incidents.
- Parking facilities. In another British city, Nottingham, just one parking deck (The Royal Moat House) accounted for about 25 percent (103) of the 415 crimes reported for all 19 downtown lots in 2001.
There are at least eight reasons why facilities are "risky" and different analysis procedures can help determine which reasons are operating in particular circumstances:
- Random Variation. It is possible to get concentrations of crime in a few places through some fluke of randomness. This is more likely to occur when you are looking at only a few facilities with few incidents. Try checking the same facilities for a different time period. If the rank order of incidents is roughly the same in both periods, then the variation is not random.
- Reporting practices. Some facilities might always report crimes to the police, while others experiencing the same number of incidents might report many fewer of them. This can be difficult to check, but you should ask officers who are familiar with the facilities whether the recorded crime rates match their own perceptions of the crime problems in the facilities.
- Many targets. Some facilities contain many targets. The store with the most shopliftings in Danvers was one of the largest in the city. But this was not the whole story because when account is taken of its size by calculating shopliftings per 100 square feet (see the final row of the table), it is still one of the riskiest for shoplifting (see Step 27).
- Hot products. A risky facility may not have a large number of targets, but it might have targets that are particularly "hot." Store 15 in the Danvers list had the highest rate of shoplifting in the city per 1,000 square feet. This store specializes in selling small, high value electronic items that meet the CRAVED criteria described in Step 31.
- Location. Facilities located in high-crime areas, perhaps where many habitual offenders live, are more likely to be crime risks. This is because offenders prefer not to travel far to commit crime (Step 16).
- Repeat victimization. Some places attract people who are particularly vulnerable to crime. Compare the people being victimized in risky and non-risky facilities. If the re-victimization rates are different, then repeat victimization may be the cause of the elevated risk (Step 29).
- Crime attractors. Facilities that draw in large numbers of offenders are crime attractors (Step 15). Crime attractors have high numbers of offenses and high offense rates. Additional diagnostic checks involve analysis of arrest records and other information containing offender names.
- Poor management. When owners or managers do not exercise proper control or management a risky facility can develop. The box shows how a slumlord's negligent management turned the properties he acquired into risky facilities (Step 44).
Reported Shopliftings by Store, Danvers, MA. October 1, 2003 to September 30, 2004
Store* | Shopliftings | Percent of Shopliftings | Cumulative Percent of Shopliftings | Cumulative Percent of Stores | Shopliftings per 1000 Sq. Ft. |
---|---|---|---|---|---|
1 | 78 | 26.2 | 26.2 | 1.3 | 1.54 |
2 | 42 | 14.1 | 40.3 | 2.6 | 0.70 |
3 | 28 | 9.4 | 49.7 | 3.8 | 0.22 |
4 | 16 | 5.4 | 55.0 | 5.1 | 0.24 |
5 | 15 | 5.0 | 60.1 | 6.4 | 0.28 |
6 | 12 | 4.0 | 64.1 | 7.7 | 0.31 |
7 | 11 | 3.7 | 67.8 | 9.0 | 0.09 |
8 | 11 | 3.7 | 71.5 | 10.3 | 0.16 |
9 | 9 | 3.0 | 74.5 | 11.5 | 0.28 |
10 | 7 | 2.3 | 76.8 | 12.8 | 2.82 |
11 | 5 | 1.7 | 78.5 | 14.1 | 0.16 |
12 | 5 | 1.7 | 80.2 | 15.4 | 0.10 |
13 | 4 | 1.3 | 81.5 | 16.7 | 0.35 |
14 | 4 | 1.3 | 82.9 | 17.9 | 0.12 |
15 | 3 | 1.0 | 83.9 | 19.2 | 3.32 |
16 | 3 | 1.0 | 84.9 | 20.5 | 0.90 |
17 | 3 | 1.0 | 85.9 | 21.8 | 0.02 |
7 stores with 2 incidents | 14 | 4.7 | 90.6 | 30.8 | 0.08 |
28 stores with 1 incident | 28 | 9.4 | 100.0 | 66.7 | 0.06 |
26 stores with 0 incidents | 0 | 0.0 | 100.0 | 100.0 | 0.00 |
Total stores = 78 | 298 | 100.0 | 100.0 | 100.0 | 0.15 |
* The top 17 stores were (in alphabetical order): Best Buy, Boater's World, Circuit City, Costco, CVS Pharmacy, Galyan's, Home Depot, Kohl's, Linens & Things, Lowe's, Marshall's, Old Navy, Radio Shack, Stop & Shop, Target, and Wal-Mart
Slumlords, Crime in Low Rent Apartments and Neighborhood Blight
Property | Year Aquired | No. of Units | Average Yearly Arrests | |
---|---|---|---|---|
Pre-Owning | Post-Owning | |||
1 | 1977 | 4 | 0 | 1.6 |
2 | 1982 | 15 | 0 | 16.9 |
3 | 1983 | 8 | 0 | 2.3 |
4 | 1985 | 8 | 0 | 4.5 |
5 | 1985 | 10 | 0.1 | 6 |
6 | 1986 | 16 | 0.2 | 27.9 |
7 | 1986 | 6/8 | 0 | 3.4 |
8 | 1987 | 5 | 0 | 8.3 |
9 | 1987 | 12 | 0 | 11.3 |
10 | 1988 | 6 | 0.4 | 8.1 |
11 | 1991 | 10 | 0.2 | 9.3 |
12 | 1991 | 10+ | 2.3 | 21.8 |
13 | 1992 | 4+ | 1.1 | 0.7 |
14 | 1992 | 4 | 0.2 | 10.7 |
In every large city, a few low-cost rental apartment buildings make extraordinary demands on police time. These "risky facilities" are often owned by slumlords - unscrupulous landlords who purchase properties in poor neighborhoods and who make a minimum investment in management and maintenance. Building services deteriorate, respectable tenants move out, and their place is taken by less respectable ones - drug dealers, pimps, and prostitutes - who can afford to pay the rent but who cannot pass the background checks made by more responsible managements. In the course of a problem-oriented policing project in Santa Barbara, California, Officers Kim Frylsie and Mike Apsland analyzed arrests made at 14 rental apartment buildings owned by a slumlord, before and after he had purchased them. The table clearly shows a large increase in the number of people arrested at the properties in the years after he acquired them. There was also some evidence that the increased crime and disorder in these properties spilled over to infect other nearby apartment buildings - a finding that supports the widespread belief that slumlords contribute to neighborhood blight.
Source: Clarke, Ronald and Gisela Bichler-Robertson (1998). "Place Managers, Slumlords and Crime in Low Rent Apartment Buildings". Security Journal, 11: 11-19.
Read More:
- Eck, John, Ronald Clarke and Rob Guerette,"Risky Facilities: Crime Concentration in Homogeneous Sets of Facilities." Crime Prevention Studies, in press.