Between 2010 and 2012 I worked on a case study of the
multi-family housing part of four neighborhoods in the city of Malmö. The main
focus of the study was on the connection of social capital/collective efficacy
and physical disorder in the form of vandalism, graffiti and arson, but fear of
crime was also discussed extensively. The study included a fairly wide array
of methods, including key informant- and focus groups interviews, systematic
social observation (SSO) of disorder and a community survey. The final report
of the project (Gerell 2013) which I submitted in august the 2012 did not (due
to time constraints) include all survey-responses that were mailed in (see
below), and did not include multi-level analysis of responses. I have since
re-visited the full data-set with some additional analysis, and in this blog
post I will present some findings related to fear of crime and avoidance behavior.
This is data that I don’t believe I will ever try to get published in an
academic journal, but I did write some up of it up for a presentation I held in
a research discussion group with members from the municipality, police, rescue
services and academia and so I might as well make it more publicly available as
well.
The neighborhoods
In the study we wanted to get a deeper understanding of
community level processes by focusing on four neighborhoods. Four adjacent
neighborhoods in the southern part of the city of Malmö were selected. Two of
the neighborhoods are included in the municipality “area programs” which are
targeted at especially troubled neighborhoods. Of the other two neighborhoods
one is made up of tenant ownership associations with a fairly old population
and the other is made up of rental apartments, about half of which are public
housing with fairly low income levels. The project was focused on multi-family
housing, and therefore excluded single-family housing present in two of the
neighborhoods and a fairly large retirement home section in one neighborhood. The total population of the studied parts of the neighborhoods is about 12 000, with the tenant ownership association neighborhood significantly smaller than the other three. A
downside to the multi-family housing focus is that official registry data is
based on the neighborhoods as a whole, and thus direct comparison to registry
data is not possible. In my report I did attempt to make some comparisons to
official data to assess whether respondents of the survey were comparable to
the population as a whole. It can be noted that among respondents there are far
too many in the oldest age group (age over 60), too many females and too few young
persons. Compared to a large survey of Malmö recently completed by my
department the differences in this study are similar, but larger.
The commmunity survey
The sample for the community survey was constructed by
mapping all addresses (each address consist of one stairwell with apartments)
in the multi-family section of the four neighborhoods (N=416), then randomly
sampling one address from each yard (N=59), and an additional 28 addresses
sampled from the remaining 357. Out of the total 87 sampled addresses entrance
was achieved to 86 which make up the final sample in the study. In each of the
86 addresses every household was included for a total of 1255 sampled
households, with a total of 689 responses (54.9%). Within households the sample
was non-random, whoever opened the door when the staff came knocking. The
community survey was performed with the aid of the city part municipality
between April and June 2012, with six persons from the studied neighborhoods
recruited to knock doors for the survey. They were recruited based on
attachment to the local community and knowledge of appropriate languages,
covering the three main language groups of residents with foreign background
living in the four neighborhoods (two interviewers each fluent in Albanian,
Arabic and Afghan languages (Pashto/Dari)). Sampled households that couldn’t be
reached received a response-envelope and instructions on how to mail their
survey in.
Research design
In order to analyze outcomes of avoidance behavior related
to fear of crime a 2-level logit regression have been performed using HLM
6 where the second level is made up of 12 micro-neighborhoods which were
constructed based on key informant interviews while taking physical and social
boundaries into account. Since the outcome variable is dichotomous the error variance is always set to pi^2/3 and ICC-values are
computed based on tau^2/(tau^2+3.289868). In the empty model ICC-values are
calculated for the outcome variable. In model 1 we add individual level
variables of demographic character that can be assumed to have an impact. In
model 2 concentrated disadvantage is added on level 2. With concentrated
disadvantage, collective efficacy and physical disorder all being strongly
correlated which may impact on the results in such a small data set we then try
collective efficacy and physical disorder independently of each other before
testing a full model. Model three thus adds collective efficacy to concentrated
disadvantage as level 2 predictor while model 4 instead of collective efficacy
introduces physical disorder. In model 5 finally we test both concentrated
disadvantage, collective efficacy and physical disorder simultaneously. It should of course be noted that the inclusion of more than one level 2 predictor for such a small number of level 2 units is questionable (Raudenbusch & Bryk 2002).
Data
The dependent variable is based on one question in a
residents’ survey in four neighborhoods of the Swedish city Malmö performed in
2012: “Have you abstained from participating in an activity due to concerns of
safety in the neighborhood where you live?” with responses graded in frequency,
“Very often”, “Often”, “Sometimes”, “No, rarely” or “Never”. The responses were
recoded so that “No, rarely” and “Never” registered as a 0 while the three
other responses were coded as a 1 (=avoidance behavior).It should be noted that "concerns of safety" is a somewhat unprecise translation to english. The actual word used, "otrygghet", literally means "not feeling safe", and it is related to the english language "fear of crime", but has a much broader meaning.
Individual level independent variables based on the survey
(for descriptives see Table below) include dummies for sex, foreign background, age
over 60, single household, length of residence over 5 years and subjective
poverty.
On the micro-neighborhood level concentrated disadvantage is
a dummy extrapolated from a grid of income levels in quartiles where a micro-neighborhood
have been assigned 1 (=concentrated disadvantage)
if a majority of the surface in the micro-neighborhood consist of grids with
over 50% of the households registered as low income according to statistics
Sweden 2008 and the remaining micro-neighborhoods coded as 0 (=no concentrated
disadvantage) (See Map below).