Overview of research on Katrina recovery in New Orleans

1. LSU Post-Katrina Research
on Disaster Recovery & Community Resilience
(Supported by the National Science Foundation)
Rick Weil
Department of Sociology, LSU
fweil@lsu.edu
www.fweil.com

2. 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

3. 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.

4. 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.

5. 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.

6. LSU Post-Katrina Research
on Disaster Recovery & Community Resilience
Hypotheses About Recovery:
Individual and Collective Resources

7. 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.
Benefit
Individual Resources (e.g. SES)
Group with Individual-
Level Resources (only)
Another Group with
Individual-Level
Resources (only)
Benefit
Individual Resources (e.g. SES)
Group with Individual-
Level Resources (only)
Group Has Collective Resources
Compensating
Effect

8. 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)

9. 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

10. LSU Post-Katrina Research
on Disaster Recovery & Community Resilience
Maps of Flooding & Damage

12. Mapped from U.S. Geological Survey Data

13. Mapped from City of New Orleans Data

14. Source: LSU Disaster Recovery Survey

15. LSU Post-Katrina Research
on Disaster Recovery & Community Resilience
Individual-Level Data Analyses

16. 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

17. 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

18. LSU Post-Katrina Research
on Disaster Recovery & Community Resilience
Aggregate Data Analyses

19. 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.

20. Aggregating 7,000 survey responses to Census Tracts.
Example: Civic Engagement

21. Sources: HUD; USPS; Valassis &
Greater New Orleans Community
Data Center
Repopulation Data (from Postal deliveries)
Can be analyzed with our aggregated survey data.

22. 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

23. Blight Reduction can be analyzed in a similar way.
Sources: HUD; USPS;
City of New Orleans

24. 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.

25. NPN Neighborhood Associations
that Responded to our Survey
Note: Some Neighborhood Associations overlap with Others

26. Blight Reduction:
1. Storm Damage
Source: City of New Orleans

27. Blight Reduction:
2. Post-Katrina Blight (average over time)
Source: U.S. Postal Service, HUD

28. Blight Reduction:
3. Blight Reduction in the Flooded Areas
Source: U.S. Postal Service, HUD

29. 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
AssociationalInvolvement .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+
OrganizationalActivities: 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

30. 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

31. 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.

32. 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

33. 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.

34. 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 other
neighborhood
organizations whose roles
overlap with your
organization
See your relationships
with 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)

35. 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

36. 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

37. LSU Post-Katrina Research
on Disaster Recovery & Community Resilience
(Supported by the National Science Foundation)
Rick Weil
Department of Sociology, LSU
fweil@lsu.edu
www.fweil.com

38. LSU Post-Katrina Research
on Disaster Recovery & Community Resilience
Addendum on Aggregate Data Analyses
(if there’s time & interest)

39. Violent Crime can also be analyzed in a similar way.

40. Church Membership
Is associated with Reduced Violent Crime
Survey Data (N = 6,945) & N.O. Police Reports, Aggregated to Tract Level (N = 182)

41. 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**