Weil, lsu post katrina survey - 150326 - southerns
Transcript of Weil, lsu post katrina survey - 150326 - southerns
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
(Supported by the National Science Foundation)
Rick Weil Department of Sociology, LSU
[email protected] www.fweil.com
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Development of Disaster Literature 1
Early literature focused on debunking myths, especially demonstrating that after disasters, the dominant community responses tended to be, not chaos and predation, but rather –
• cooperation and altruism
• with new solidaristic organizations often emerging from the grass roots
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Development of Disaster Literature 2
Beginning around the 1970s, focus in the literature turned to the effects of inequality and vulnerability.
• Weaker social and economic groups were more vulnerable to harm, especially the poor, minorities, women, children and the elderly, and disabled people.
• In addition, due to factors like environmental racism and government favoritism, disadvantaged groups were more exposed to hazards in the first place and less likely to receive assistance after a disaster.
• At a macro-level, vulnerability research has moved to a critique of Neo-liberalism.
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Development of Disaster Literature 3
Most recently, scholars have begun emphasizing social capital, civic engagement, and the importance of organizations.
• e.g., Daniel Aldrich’s recent book on social capital and disaster recovery.
• Social capital augments analyses of inequality and vulnerability; it does not displace them.
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Roots of Social Capital theory in Political Sociology
Early empirical work from the 1950s and 1960s set the basis for understanding civic engagement.
• Especially the work of Sidney Verba.
• Putnam’s work on social capital grew out of this.
• It points back to Tocqueville’s discussion of how community self-governance works.
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
Hypotheses About Recovery: Individual and Collective Resources
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The Verba-Nie-Kim Hypotheses: Individual & Collective resources are correlated,
but Collective Resources can Compensate for the Lack of Individual Resources
Derived from: Sidney Verba, Norman H. Nie, Jae-on Kim, Participation and Political Equality: A Seven-Nation Comparison. Cambridge: Cambridge UP, 1978, page 85.
Be
ne
fit
Individual Resources (e.g. SES)
Group with Individual-Level Resources (only)
Another Group with Individual-Level Resources (only)
Be
ne
fit
Individual Resources (e.g. SES)
Group with Individual-Level Resources (only)
Group Has Collective Resources
Compensating Effect
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New Orleans Hypotheses: Individual & Collective Resources
and Disaster Recovery
Individual-Level Resources
Yes No
Collective
Resources
(Social Capital,
Organization)
Yes
High level of Recovery. High to Medium level of
Recovery.
e.g. Jewish community e.g. Vietnamese community;
SAPC members
No
High to Medium level of
Recovery. Low level of Recovery.
e.g. Renaissance Village
(FEMA Trailer Park)
(Rare: High Individual-Level
Resources usually permit
formation of Collective Resources, as needed)
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
Data Basis:
7,000 interviews in main Household Survey over 10,000 total interviews, all surveys
ca. 100 interviews with Neighborhood Association Leaders Ethnographic research with over 200 groups
ca. 150 Videotaped in-depth interviews
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
Maps of Flooding & Damage
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Mapped from U.S. Geological Survey Data
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Mapped from City of New Orleans Data
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Source: LSU Disaster Recovery Survey
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
Individual-Level Data Analyses
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Individual Level Regressions: Low Damage, High Social Status, & Social Capital
Promote Recovery and reduce Negative Outcomes.
Stay or Leave
Nola
Recovery -
Household
Recovery -
Neighborhd
Psych
Distress
Social
Closeness
Damage & Resources
Damage to Residence -.10** -.23** -.37** .14** -.03*
Demographic
Estimated Income .04* .15** .09** -.14** -.07**
Black .07** -.10** -.01 -.10** .14**
Female .05** -.04* -.02+ .12** .03+
Age .06** -.06** -.06** .00 .06**
Time since Katrina .14** .25** .24** -.07** .05**
Social Capital
Social Trust .12** .14** .18** -.18** .25**
Civic Engagement .04* .01 .01 .05** .12**
Social Embeddedness -.04* .07** .04* -.02 .14**
Church service attendance -.02 .01 -.04** -.07** .10**
Adj R-Sq .05 .18 .24 .10 .15
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Individual Level Regressions: “Intersectionality” has a small, irregular impact,
but it doesn’t change the main story.
Stay or Leave
Nola
Recovery -
Household
Recovery -
Neighborhd Psych Distress
Social
Closeness
Damage & Resources
Damage to Residence -.10** -.10** -.23** -.23** -.37** -.37** .14** .14** -.03* -.03*
Demographic
Estimated Income .01 .03+ .12** .13** .09** .09** -.10** -.13** -.06** -.07**
Black .12** .08** -.07** -.09** .03 .00 -.12** -.11** .15** .14**
Female .07** .07** -.04+ -.03+ -.02 -.02 .14** .12** .06** .03+
Age .05** .05** -.06** -.06** -.07** -.06** .00 .00 .06** .06**
Time since Katrina .14** .14** .25** .25** .24** .24** -.07** -.07** .05** .05**
Social Capital
Social Trust .12** .12** .14** .14** .18** .18** -.18** -.18** .25** .25**
Civic Engagement .04* .04* .01 .01 .01 .01 .05** .05** .12** .12**
Social Embeddedness -.04* -.04* .07** .07** .04* .04* -.02 -.02 .14** .14**
Church service attendance -.03 -.02 .01 .01 -.04** -.04** -.06** -.07** .10** .10**
Intersectionality
Black Female -.04 -.01 -.04 -.02 -.04+
Poor Female .01 .02 .05** -.02 -.02
Poor Black -.08** -.07** -.06** .09** .03
Poor Black Female -.04* -.04* -.02 .03 .00
Adj R-Sq .06 .06 .18 .18 .24 .24 .10 .10 .15 .15
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
Aggregate Data Analyses
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With a large enough N (7,000), we can aggregate (average) data to geographical districts and conduct aggregate analyses.
We use Census Tracts, the finest (smallest) district size we can, consistent with reliable averages per district.
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Aggregating 7,000 survey responses to Census Tracts. Example: Civic Engagement
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Sources: HUD; USPS; Valassis & Greater New Orleans Community
Data Center
Repopulation Data (from Postal deliveries) Can be analyzed with our aggregated survey data.
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Aggregate Level Bivariate Charts: Low Damage, High Social Status, & Social Capital
Promote Repopulation per Census Tract*
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Pre-K 3/09 3/10 3/11 3/12
Civic Engagement
Top Civ Eng Bottom Civ Eng
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Pre-K 3/09 3/10 3/11 3/12
Income
Top Assets Bottom Assets
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Pre-K 3/09 3/10 3/11 3/12
Damage
Top Damage Bottom Damage
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Pre-K 3/09 3/10 3/11 3/12
Social Embeddedness
Top SocEmb Bottom SocEmb
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Pre-K 3/09 3/10 3/11 3/12
Race
Most Black Least Black
*Showing top and bottom quartiles
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Blight Reduction can be analyzed in a similar way.
Sources: HUD; USPS; City of New Orleans
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We add an Organizational Level: A Survey of Neighborhood Association Presidents (N=70)
In collaboration with The Neighborhoods Partnership Network (NPN), A nonprofit, citywide network of neighborhoods.
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NPN Neighborhood Associations that Responded to our Survey
Note: Some Neighborhood Associations overlap with Others
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Blight Reduction: 1. Storm Damage
Source: City of New Orleans
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Blight Reduction: 2. Post-Katrina Blight (average over time)
Source: U.S. Postal Service, HUD
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Blight Reduction: 3. Blight Reduction in the Flooded Areas
Source: U.S. Postal Service, HUD
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Blight Reduction: Neighborhood Associations’ Effect on Reducing Blight:
Multiple Regressions
LSU/NPN Survey of Neighborhood Association Leaders (N = 67)
and LSU Disaster Recovery Survey (N = 7,000)
Regressions (with Fixed Controls)
Blight Reduction
Wet areas: all Wet areas: NBOs only
1 2 3 4 5 1 2 3 4 5
Damage Assessment .277+ .189 .328* .259+ .318*
Median household income .006 .074 .021 .101
Unemployed -.457* -.302+ -.442* -.438* -.222 -.433*
Pct Black .324 .308* .302 .260 .344* .394+ .383* .384+ .294 .409*
Married with Children .328+ .341* .333+ .364*
Pct Owner Occupied -.276 -.316+ -.281 -.327+
Disadvantage Index -.168 -.243 -.149 -.262
Associational Involvement .271 .411** .260+ .291+ .407** .199 .437** .222 .218 .401**
Family is Rooted in New Orleans .179 .254 .268 .341+
Church service attendance -.215 -.090 -.248 -.083
Cooperation with Other Organizations: Count .090 .274* .180 .160 .281* .025 .202 .144 .047 .215+
Organizational Activities: Blight (q 41) .321* .240* .242* .295* .223+ .361** .308* .262* .353** .267*
Organization Structural Assets (Block Capts) .117 .157 .148 .217+
Adj R-Sq .602 .567 .607 .560 .553 .658 .577 .641 .621 .582
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
Causal Processes/Mechanisms: Community Strategies and Resources
for Recovery
Qualitative Research: “Social Action” Partnerships
and Video Ethnography
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Community Strategies and Resources for Recovery 1
• Increasing organizational capacity and autonomy.
– Use of Committees, Block Captains, etc.
– Doing own Data Collection.
– New technologies, like Mapping, Data Bases.
– Use of Volunteers.
– Taking the initiative and not waiting for outside help.
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Community Strategies and Resources for Recovery 2
• Greater strategic sophistication.
– Creating “Critical Masses” or “Tipping Points”
• Talking to Retail & Neighbors
• Managing expectations
– Branding
– Community planning
• E.g., Broadmoor, Vietnamese, Jews
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Managing Expectations and Tipping Points May have spurred Repopulation
Note: Tracts are different in different years
The Effect of Expectations on Repopulation in Greater New Orleans, 2006-2010
Survey Data (N=ca. 7,000) & USPS Data at Tract Level (N as shown)
Bivariate Correlations
Cumulative Rate of Repopulation to:
Expectations N 2006 2007 2008 2009 2010
Most NBH evacuees will return 2007 33 - .212 .312+ .317+ .322+
Most NBH evacuees will return 2008 37 - - .165 .128 .091
Neighborhood will Recover 2006 23 .584** .602** .708** .716** .742**
Neighborhood will Recover 2007 33 - .596** .609** .628** .604**
Neighborhood will Recover 2008 37 - - .082 .153 .142
0.40
0.60
0.80
1.00
Pre-K 3/09 3/10 3/11 3/12
Civic Engagement
Top Civ Eng Bottom Civ Eng
Managing expectations might have spurred repopulation in communities
that were well organized.
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Community Strategies and Resources for Recovery 3
• Increasing citizen participation. – People who had never participated before
• A new Cooperative Orientation among community leaders – 91% of
Neighborhood leaders affirmed that relations with other leaders are cooperative
0%
20%
40%
60%
80%
100%
There are otherneighborhood
organizations whose rolesoverlap with your
organization
See your relationshipswith other neighborhood
groups as cooperative,rather than competitive
Your organization compares activities and
strategies with organizations in other
neighborhoods, in order to learn from each others’
experiences
Relations among Neighborhood Associations (N = 56)
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Community Strategies and Resources for Recovery 4
• Emergence of new Umbrella Groups from outside the organizational eco-system they work with
– Convening Groups.
– Find areas of common concern on which they can work together.
– Find synergies on issues that would otherwise produce competition/conflict.
– Learn from each other. Barbara Lacen Keller teaching NPN’s Capacity College
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Community Strategies and Resources for Recovery 5
• New recovery resources from “Outside-inside” the community – Extra-Regional, National, & International
assistance from within the communities
– Vietnamese Community • Houston & West Bank Neighbors
– Jewish Community • National & Baton Rouge organizations
– Cultural Community • Assistance to Musicians from Musicians
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
(Supported by the National Science Foundation)
Rick Weil Department of Sociology, LSU
[email protected] www.fweil.com
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LSU Post-Katrina Research on Disaster Recovery & Community Resilience
Addendum on Aggregate Data Analyses (if there’s time & interest)
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Violent Crime can also be analyzed in a similar way.
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Church Membership Is associated with Reduced Violent Crime
Survey Data (N = 6,945) & N.O. Police Reports, Aggregated to Tract Level (N = 182)
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Aggregate Level: Church Membership’s Effect on Reducing Violent Crime:
Spatial Regressions
Factors Influencing Crime Rates in Orleans Parish, 2007-2009
Survey Data (N = 6,945) & Aggregate Data at Tract Level (N = 182)
Regression Models, Testing for Spatial Auto-correlation: t-Statistics or z-values
Natural Log (Ln) Rates Combined Murder Assault
Constant 4.813** 1.925+ 3.506**
Spatial Lag 13.024** 9.740** 10.662**
ACS 2005-09 Pct Below Poverty level 2.149* 2.305*
ACS 2005-09 Unemployed over Age 16 -3.360**
ACS 2005-09 Pct Age 15-34 -1.197
ACS 2005-09 Pct Vacant Housing Units 4.181** 2.362*
ACS 2005-09 Pct Owner Occupied -1.004 -3.812**
ACS 2005-09 Pct Non-Hispanic Black 3.096** 4.024** 3.327**
Church member -3.343** -2.914** -4.293**
Social Trust -3.594** -2.227* -2.968**