Is Social Cohesion the missing link in overcoming violence, inequality and poverty? Laboratory for the Analysis of Violence State University of Rio de Janeiro (LAV-UER)
Social Cohesion • Polysemic and Contested Concept • Cohesion through similarity (value-based or socio-economic), analogous to equality • Cohesion through mutual links regardless of similarity 2
Social Cohesion • Our choice based on 5 dimensions: • Sense of Belonging/ Identification • Trust • Cooperation (real or hypothetical ) • Social Interaction (frequency and quality) • Participation in social organisations • Collective Efficacy 3
Social Cohesion • Can be defined at many levels: • National • Regional • Local • Our choice is social cohesion at the local level – also because UPP act at a local level 4
Structural Correlates of municipal homicide rates • N= 238 municipalities with 100.000 inhab. or + in 2010 Census • Small municipalities have very unreliable homicide rates • Violence is mostly an urban phenomenon • Data at the municipal level collected from many sources • Age-sex standardised homicide rates • Logarithmic transformation 5
Structural Correlates of municipal homicide rates • Dimensions: • Demographic factors: structure and dynamics • Socioeconomic factors: income, poverty and income inequality • Labour market: activity, unemployment and informality • Education: educational level, access to school and student flows • Urban services and living conditions • Family vulnerability 6 • Lifestyles • Public policies and municipal expenditures
Structural Correlates of municipal homicide rates Table 2: Pearson Correlation Coefficient between Standardized Homicide Rate in 2010 and Income Indicators calculated in different years INCOME CALCULATED FOR INCOME INDICATORS THE FOLLOWING YEAR 1991 2000 2010 Average per capita income -0,43 -0,41 -0,36 Average per capita income of those in extreme poverty -0,22 -0,38 -0,09 Average per capita income of those in the 1st (poorest) -0,55 -0,55 -0,5 i til Average per capita income of those in the 2nd quintile -0,53 -0,52 -0,49 Average per capita income of those in the 3rd quintile -0,49 -0,48 -0,45 Average per capita income of those in the 4th quintile -0,44 -0,42 -0,38 Average per capita income of those in the 5th quintile -0,36 -0,35 -0,28 7 Average per capita income of the richest decile -0,34 -0,34 -0,27
Structural Correlates of municipal homicide rates Table 3: Multiple Regression Model on municipal logged standardized homicide rates in 2010 Standard P-value β Independent Variables B Error t (sig) 1,794 0,504 3,559 0,000 Constant 0,182 0,034 0,209 5,299 0,000 Logarithm of population (2010) 'Demographic Dynamics' from 1990 to 2000 0,089 0,029 0,127 3,11 0,002 Per capita Household Income of the poorest quintile in 1991 -0,007 0,001 -0,410 -7,324 0,000 Net Enrolment Rate for High School (2010) -0,025 0,005 -0,300 -5,539 0,000 % of population with inadequate water and/or sanitation -0,02 0,005 -0,175 -3,845 0,000 (2010) % of Women aged 15 to17 with children (2010) 0,091 0,016 0,290 5,86 0,000 Rate of people who commuted into the municipality (2010) 0,024 0,005 0,221 4,544 0,000 % of people who commuted outside the municipality (2010) 0,009 0,003 0,120 2,743 0,007 % of people who declare themselves evangelical (2010) 0,014 0,004 0,143 3,632 0,000 Per capita municipal spending on Culture (2008-2010) -0,006 0,002 -0,108 -2,347 0,020 8 Existence of a Municipal Security Council (2009) 0,193 0,054 0,134 3,589 0,000
Impact of Social Cohesion on Fear of Crime • Surveys with questions on fear of crime and also with items that could be identified as belonging to social control • Only 4 victimisation surveys identified and available: • Metropolitan Region of Rio de Janeiro • State of Mato Grosso • Metropolitan Region of Goiania • City of Belo Horizonte • Different times and different questionnaires • Fear of crime measured as: • a) feeling of insecurity while walking the streets during the day; 9 b) feeling of insecurity while walking the streets at night.
Impact of Social Cohesion on Fear of Crime Figure 1 – Percentage of respondents who felt unsafe while walking the streets during the day and at night: Metropolitan Region of Rio de Janeiro (2008), state of Mato Grosso (2010), Metropolitan Region of Goiania (2007) and city of Belo Horizonte (2002) 90% 84% 80% 70% 70% 60% 54% 49% 50% 40% 29% 26% 30% 20% 14% 10% 0% During the Day During the Night During the Day During the Night During the Night During the Day During the Night Metropolitan Region of Rio de Janeiro State of Mato Grosso Metropolitan City of Belo Horizonte 10 Region of Goiania
Impact of Social Cohesion on Fear of Crime: main results • Two dimensions of social cohesion appeared to have weak links to reduced fear of crime: • trusting one's neighbours and willingness to help a neighbour • the ability to distinguish neighbours from strangers in the street. This speaks to questions of familiarity in local environments. • However, impact is small and not consistent or robust over different places or ways to measure the dependent variable 11 • Weak support for the hypothesis that social cohesion may reduce fear of crime
Social Cohesion and the UPP Project • Field research in two poor communities: • Tabajaras: in rich area and relatively calm after UPP introduction • Cidade de Deus: in poor area and still with high levels of violence • Different Results: • In Tabajaras: police are now the social regulators and have displaced drug dealers in this function • In Cidade de Deus: police and drug dealers share a regulating function. Community members feel 12 ‘trapped’ between both actors and fearful of reprisals
Social Cohesion and the UPP Project • In Tabajaras: reduction of violence has attracted new relatively wealthier residents (gentrification) which has undermined social cohesion (less trust, less mutual contact, newcomers are said to be unaware of local customs) • In Cidade de Deus: police now receive funding for social projects, thus displacing old community associations (reduction of social cohesion) 13
Social Cohesion and Violence • Lack of clear support for the social cohesion – violence reduction hypothesis • Social Efficacy Theories (Sampson) assume: • Strong state • Normative Consensus • Lack of normative challenges and concurrent legitimacies • In our contexts: • Weak states 14 • Ambivalent role of the police • Domination by illegal groups
Social Cohesion and Violence • Spontaneous action by the community may be guided by illegal means or aims: lynching or demand for the ‘owner of the hill’ – thus it may reduce but also foster violence • In informal setting in the Global South (slums etc.) strong social ties may co-exist with high levels of violence, against collective efficacy theory 15
Recommend
More recommend
