neighborhood recovery in new orleans

8/14/2019 Neighborhood Recovery in New Orleans

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Neighborhood Recovery in Post-Katrina New Orleans

An Essay Presented

by

Thomas Shade Wooten

to

The Committee on Degrees in Social Studies

in partial fulfillment of the requirements

for a degree with honors

of Bachelor of Arts

Harvard College

March 2007


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Table of Contents

Introduction..................................................................................................................................... 1Explaining Divergent Rates of Neighborhood Recovery ....................................................... 1Why Study Neighborhood Recovery Efforts in New Orleans? .............................................. 4

The Course of This Thesis ...................................................................................................... 6

Chapter 1: Recovery Variables and Methodology........................................................................ 10I. Explaining Disaster Recovery ............................................................................................... 10

Individual-Context Recovery Variables ............................................................................... 11Group Context Variables ...................................................................................................... 17

II. Methodology ........................................................................................................................ 28Comparative Analysis of Broadmoor, Gentilly, and Lakeview............................................ 28Interview and Participant Observation-Based Research....................................................... 33

Chapter 2: Neighborhood Comparison ......................................................................................... 35

I. Introducing Broadmoor, Gentilly, and Lakeview.................................................................. 35Broadmoor ............................................................................................................................ 36Gentilly ................................................................................................................................. 37Lakeview............................................................................................................................... 39Katrinas Effects ................................................................................................................... 41

II. Divergent Recovery Outcomes ............................................................................................ 42III. Explaining Divergent Recovery Outcomes ........................................................................ 49

Rationale for these dependent variables ............................................................................... 50Testing the variables ............................................................................................................. 52

Chapter 3: Resident-Driven Recovery Efforts.............................................................................. 62I. Resident-Driven Recovery Efforts in Broadmoor, Lakeview, and Gentilly ......................... 63

Broadmoors Effort............................................................................................................... 63Lakeviews Effort ................................................................................................................. 69Gentillys Effort .................................................................................................................... 73

II. Explaining Resident Return ................................................................................................. 78Hurdles to Recovery ............................................................................................................. 79Overcoming Recovery Hurdles............................................................................................. 81

Chapter 4: How and Why Resident-Driven Recovery Efforts Succeed ....................................... 91Variables that Explain Movement Emergence and Success................................................. 92

I. Leadership and Resident Mobilization.................................................................................. 93II. Residents Generate and Implement Recovery Plans............................................................ 98III. Partnerships and Outside Resources ................................................................................. 104IV. Adaptive Capacity ............................................................................................................ 109

Conclusion .................................................................................................................................. 116

Sources Consulted....................................................................................................................... 120


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Introduction

Explaining Divergent Rates of Neighborhood Recovery

Broadmoor, Gentilly, and Lakeview are three residential neighborhoods of New Orleans

that were badly flooded in the wake of Hurricane Katrina. In the two and a half years since the

storm, Broadmoor and Lakeview have mounted successful recoveries, with residents returning

and rebuilding their homes at consistent rates across both neighborhoods. In Gentilly, by

contrast, recovery has been inconsistent, with the most heavily damaged portions of the

neighborhood experiencing slow or stagnant rates of resident return. These divergent outcomes

are not easily explained by demographic differences between the neighborhoods, nor by any

difference in the degree of damage each suffered. Broadmoors success, for example, comes in

spite of the fact that its residents had by far the highest rate of poverty (31.8%) and the lowest

average household income ($36,400 per year) of the three neighborhoods prior to the storm

(GNOCDC).1

Lakeviews success comes in spite of the fact that its homes suffered the most

consistent and severe damage of houses in the three neighborhoods, necessitating more than

three times the percentage of home demolitions (27.8% of Lakeview properties as of July of

2007) than was needed in either Gentilly (8%) or Broadmoor (2.3%), (Ahlers 2007; Jett 2007;

Lakeview 2007). Why then, have Broadmoor and Lakeview experienced consistent residential

recoveries, while Gentilly has not?

Some literature on disaster recovery would suggest that the explanation for these

divergent recovery outcomes lies in structural differences between the neighborhoods.

1 A substantial portion of the demographic data in this thesis was obtained from the Greater New Orleans DataCenter websites archive of pre-Katrina data. The website provides comprehensive data from the 2000 census forevery New Orleans neighborhood, and was thus an invaluable resource.


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Prevailing pre-disaster economic trends and available monetary resources among disaster-

affected populations, for example, have been found to be key predictors of the rate of post-

disaster recovery (Haas, 1977). Other demographic variables, including the portion of renters in

affected populations and the racial makeup of these groups, have been found to be important

predictors of the speed of recovery as well (Elliott, 2006). Conversely, other disaster recovery

literature would seek the explanation for the divergence in recovery outcomes between these

three neighborhoods by examining the structure and implementation of recovery efforts within

each. For example, the degree of control residents exert over recovery efforts, the nature of

leadership structures within each neighborhood, and the relationships between residents and

higher levels of government could all affect each neighborhoods rate of recovery (Bolin, 1998),

(Nakagawa, 2004), (Peterman, 2000).

In this thesis, I show that structural variables do not convincingly explain the difference

between Gentillys inconsistent recovery and the consistent recoveries in Broadmoor and

Lakeview. Rather, I argue that the presence of successful resident-driven recovery efforts in

Broadmoor and Lakeview and the absence of a similarly successful effort in Gentilly

convincingly explains why the former two neighborhoods have experienced more consistent

recoveries. Recovery initiatives in Broadmoor and Lakeview have sustained widespread resident

engagement and successfully implemented an array of concrete recovery initiatives from

reopening neighborhood schools to hiring case workers to help individual residents return

whereas Gentillys resident-driven recovery efforts have not. I show that the broad-based and

results-oriented recovery efforts in Lakeview and Broadmoor have substantially lowered

motivational, logistical, and material hurdles to resident return in these neighborhoods, whereas

efforts in Gentilly have not had similar effects. Specifically, I argue that the process of


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undertaking recovery efforts in Broadmoor and Lakeview, which requires the involvement of

hundreds of residents spending thousands of hours working together to plan and implement

neighborhood recovery initiatives, has done as much to spur resident return in these

neighborhoods as the concrete outcomes that these resident efforts produce.

I also explain why and how efforts in Broadmoor and Lakeview have successfully grown,

sustained themselves, and achieved their goals, while Gentillys resident-driven effort has not. I

argue that the success of recovery efforts in Broadmoor and Lakeview stems from the existence

of residents associations in these neighborhoods prior to the storm, which provided residents

with both established leadership and repertoires of collective action in the storms wake that

Gentillys residents lacked. This prior organization, combined with a heightened sense of

urgency that residents in Broadmoor and Lakeview felt relative to residents of Gentilly, spurred

Broadmoor and Lakeview residents to take responsibility for their neighborhoods recoveries

themselves, whereas the absence of these factors in Gentilly caused residents to remain

dependent upon outsiders to spur and guide their neighborhoods recovery. Resident

mobilizations in Broadmoor and Lakeview spawned recovery efforts that were characterized by

full resident control over planning, close connections between planning and implementation,

partnerships that supported resident efforts, and a great deal of adaptive capacity. These

characteristics allowed the efforts in Broadmoor and Lakeview to sustain high levels of resident

engagement and achieve their stated goals, thereby helping to lower both motivational and

material barriers to individual resident return in the two neighborhoods.

My findings are important because they suggest that the recovery successes of

Broadmoor and Lakeview are not solely the product of any inherent structural advantages the

two neighborhoods hold, and could therefore be replicable in other residential areas of New


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Orleans. Indeed, the similarities between the resident-driven recovery efforts in Broadmoor and

Lakeview, which I outline above and explore in subsequent chapters, suggest a formula for

successful neighborhood recovery in the otherwise stagnant post-Katrina environment.

Why Study Neighborhood Recovery Efforts in New Orleans?

Neighborhood recovery efforts in New Orleans are worth studying because they are

among the few forces within the city that have consistently driven its recovery forward.

Otherwise, few success stories have emerged from New Orleans in the two and a half years since

80% of the city was flooded in the wake of Hurricane Katrina. The return of residents to the city

and the rebuilding of homes have been slow. The latest available figures show that over 58,000

addresses in the city (nearly 30% of Orleans Parish households) were still not receiving mail in

November of 2007, indicating the high number of properties that remain unoccupied in the wake

of the storm (GNOCDC 2008). In addition to abandoned properties and displaced residents, the

city faces a host of other problems. Murders in the city spiked after the storm, and the Orleans

Parish district attorneys office found itself without the capacity to keep pace; it won just one

conviction for the 162 murders committed in all of 2006 (Brown 2007). Infrastructure

throughout the city is crumbling: roads are in severe disrepair, and sewer and gas lines that were

corroded by Katrinas salty floodwaters are failing at high rates. Many public schools in the city

have yet to reopen, and in some cases, their empty buildings remained full of moldy debris even

two years after the storm (Reckdahi 2007). The city faces many daunting challenges to

overcome.

Unfortunately, leadership and support from all levels of government since the storm has

left much to be desired in the face of these challenges. Three citywide recovery planning

processes the Bring New Orleans Back (BNOB) plan, the Lambert Plan, and the Unified New


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Orleans Plan (UNOP) have been undertaken in attempts to create unifying visions to guide the

citys recovery, but few of the initiatives these plans propose seem likely to receive funding

(Ikeda and Gordon 2007: 5; Reichard 2007: 9). In 2007, the budget for the citys Office of

Recovery and Development Administration, which spearheads recovery projects in flooded areas

of the city, was only $117 million (Krupa 2007). By contrast, repairs on the citys football

stadium alone were projected to cost $140 million (SMG 2006: 1). Moreover, a federally funded

program to compensate homeowners for flood damage faced a $6.6 billion shortfall in September

of 2007, and though the gap was eventually closed by Congress, tens of thousands of applicants

have yet to see the money they were promised (Hammer 2007). In all, leadership and resources

for the New Orleans recovery have not been readily forthcoming from the city, state, or federal

governments.

New Orleans is a city made up of well defined neighborhoods (Campanella 2006: 164),

and residents in many of these neighborhoods have organized in Katrinas wake to fill the void

of government initiative and spearhead their own recovery initiatives. Residents associations

across the city have done everything from forming neighborhood school committees to reopen

public schools as charter schools, to spearheading thorough inventories of infrastructural

problems within their borders, to opening recovery centers that aim to ease returning residents

renovations of their flooded homes and transitions back into their neighborhoods. In a sign of

how much power and initiative has shifted away from the city government and into the hands of

organized neighborhoods, Broadmoors Community Development Corporation recently hired a


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worker to oversee the city governments handling of grant money the neighborhood received

(Hal Roark, February 29, 2008).2

The level of resident organization and initiative that has sprouted up from New Orleans

neighborhoods is certainly unprecedented in the citys history, if not in the history of the United

States (Ikeda and Gordon 2007: 11; Irazabal and Neville 2007: 131). Irazabal and Neville

describe the frequent use of the term citizens revolution to describe active resident

involvement in recovery initiatives, and note that resident-driven efforts in the storms wake

have not been well studied or documented (Irazabal and Neville 2007: 131). My research,

therefore, focuses on a significant but largely unstudied phenomenon in the New Orleans

recovery process. As a result, although my writing remains in dialog with currently-existing

literature about disaster recovery, urban neighborhoods, and community-based development, its

primary aim is to explore the neighborhood-based recovery work being undertaken by New

Orleans residents, and to explain why and how some resident-driven recovery efforts in the city

are succeeding. This work is well worth undertaking, as it has direct practical significance to

Gulf Coast communities currently trying to rebuild, as well as to communities that fall victim to

future disasters.

The Course of This Thesis

In Chapter 1, I draw from literature about disaster recovery to identify a number of

variables that could explain the divergent recovery outcomes between Broadmoor, Gentilly, and

Lakeview. I show that these potential factors include variables that affect recovery on an

individual-by-individual basis and also variables that affect the emergence and eventual success

2 A complete list of interviews is available at the end of this thesis. Unless interviewees granted me explicitpermission to use their names, I have given them single first name pseudonyms. In this case, Hal gave mepermission to use his real name.


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of collectively-based recovery efforts. I then argue that my comparative methodology and

reliance on interviews and firsthand observation provide an optimal basis upon which to test the

variables I identify while also developing in-depth qualitative pictures of the realities of each

neighborhoods recovery.

In Chapter 2, I introduce Broadmoor, Gentilly, and Lakeview. Then, I show that

Broadmoor and Lakeview have experienced residential recoveries that are both spatially and

temporally consistent, while Gentillys residential recovery has been spotty. Subsequently, I

undertake a rigorous cross-neighborhood comparison of variables that potentially affect the rates

of recovery in Broadmoor, Gentilly, and Lakeview, and through this comparison, identify

variables that could explain the neighborhoods divergent recoveries. I posit that the success of

resident-driven efforts in Broadmoor and Gentilly at maintaining broad bases of resident

involvement and implementing an array of recovery initiatives, versus the failure of Gentillys

efforts on these fronts, explains Broadmoors and Lakeviews more consistent rates of rebuilding

and resident return.

In Chapter 3, I substantiate my argument that the difference in recovery outcomes

between the three neighborhoods is attributable to the success of resident-driven efforts in

Broadmoor and Lakeview at maintaining high resident involvement and implementing a number

of projects to spur recovery within their borders. I first lay out the sequence of events by which

residents in Broadmoor, Gentilly, and Lakeview mobilized in the wake of the storm, planned

their responses to the disaster, and then, in the cases of Broadmoor and Lakeview, implemented

their plans. Drawing on interview data from conversations with residents, I then show that

resident-driven efforts in Broadmoor and Lakeview have substantially lowered both motivational

and material hurdles to resident return, whereas Gentillys effort has not. Specifically, I show


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that widespread and active resident engagement in these efforts increased residents confidence

and motivation to move back to Broadmoor and Lakeview, and that the outcomes of these efforts

lowered material and logistical hurdles to resident return in both neighborhoods. I argue that this

difference in outcome provides a compelling explanation of the difference between Gentillys

inconsistent recovery and the consistent recoveries taking place in Broadmoor and Lakeview.

Finally, in Chapter 4, I explore why and how efforts in Broadmoor and Lakeview have

successfully maintained high rates of resident engagement and implemented an array of recovery

projects, while Gentillys effort failed in this regard. I show that the prior existence of residents

associations in Broadmoor and Lakeview gave residents of both neighborhoods established

leadership and repertoires of collective action that Gentillys residents lacked. I argue that these

initial advantages, combined with several specific focusing events that instilled residents with

a sense of urgency, led Broadmoor and Lakeview residents to mobilize rapidly and realize that

they themselves would be largely responsible for driving their neighborhoods recoveries

forward. Their senses of urgency and responsibility, in turn, led them to undertake recovery

efforts characterized by resident control over neighborhood planning, a close connection between

planning and implementation, the formation of an array of constructive partnerships to support

neighborhood efforts, and a great deal of adaptive capacity. It was these characteristics, I argue,

that allowed recovery efforts in Broadmoor and Lakeview to maintain high rates of active

resident involvement and achieve their goals. In Gentilly, by contrast, I show that the lack of an

existing residents association, combined with the lack of a defining event to quickly draw

residents together and instill them with a sense of urgency, led to a gradual mobilization in which

residents did not fully grasp that Gentillys fate lay largely in their hands. As a result, their

attempts to spur recovery forward remained largely dependent upon the initiative and guidance


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of outsiders, and they failed to develop the capacity to implement projects themselves.

Consequently, I argue, their efforts failed both to implement recovery projects and to maintain

widespread resident engagement the two key ways in which this effort could have lowered

hurdles to resident return.


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Chapter 1: Recovery Variables and Methodology

In this chapter, I draw from literature about disaster recovery, neighborhood-driven

development, and the particular recovery dynamics in New Orleans since Hurricane Katrina. I

use this review of literature to argue for the relevance and appropriateness of my focus on

Broadmoor, Gentilly, and Lakeview, my explicitly comparative analytic framework, and my

dependence upon interviews, participant observation, and readily available demographic and

repopulation data for the bulk of my research. I show that current literature about disaster

recovery suggests a number of variables that can both aid and hinder disaster recovery, and argue

that my analysis of Broadmoor, Gentilly and Lakeview through a comparative framework allows

the effects of many of these variables to be tested. Specifically, I argue that this approach allows

me to simultaneously test variables that affect recovery on an individual-by-individual basis and

variables that affect the emergence and success of collective recovery efforts which implement

initiatives to expedite individual recovery. Finally, drawing on Petermans criteria for doing

successful neighborhood development, (Peterman 2000: 155), I argue that my methodology

must not only allow me to establish whether or not neighborhood-based recovery efforts are

affecting recovery, but why and how they are successful if this is indeed the case. I show that my

choice of neighborhoods, my on the ground research, and my comparative analytical

methodology are well suited to this task.

I. Explaining Disaster Recovery

What drives recovery from a disaster? What variables can speed it along, or conversely

hinder it? A number of authors have weighed in on these questions, and their work provides a

diverse array of sometimes contradictory answers. All of their insights are valuable, however,


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because they propose variables that could affect recovery, which I must in turn test. For the

purposes of presentation in this chapter, I separate these recovery-affecting variables into two

broad categories: variables that apply at the neighborhood or city level but primarily affect

recovery on an individual by individual basis, and variables that affect the emergence or

effectiveness of collectively-based responses to disaster. Ultimately, if I am to prove that

resident-driven recovery efforts in the neighborhoods I study are having profound effects upon

their recoveries, I must provide a convincing account of why an array of potentially important

structural variables do not sufficiently explain the recovery outcomes in Broadmoor, Gentilly,

and Lakeview. I must also explain how and why Broadmoor and Lakeview have seen their

resident-driven recovery efforts succeed, while Gentillys effort has floundered. To undertake

these tasks, I must take account of variables that could be used to explain both of them.

Individual-Context Recovery Variables

Several authors have posited explanations of disaster recovery that place little emphasis

on direct human agency within disaster-affected communities, arguing instead that the speed and

thoroughness of recovery is largely a function of pre-existing economic trends, the immediate

availability of recovery resources, and pre-existing social and political structures. As the authors

conceive them, these factors apply throughout a disaster-affected area or population, but

primarily affect recovery on an individual-by-individual basis. In this section, I identify of such

variables in order to put their explanatory power to test in the next chapter.3

In a comparative study of the recoveries of 44 Southern Italian villages conducted after a

severe 1980 earthquake, for example, Ino Rossi concludes that only structural variables affect

the rate of recovery between communities. Rossi employs a dataset that was collected five years

3 I include a chart at the end of this section summarizing the variables and the authors who propose them.


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after the earthquake took place, which consists of 43 variables for each of the villages under

study (Rossi 1993: 2-8). These variables include both dependent measures of recovery

outcomes and independent variables that could have some bearing on recovery. Within the

category of independent variables, Rossi further differentiates between what he calls action

variables, such as measures of perceptions of mayoral leadership in the disasters wake, and

structural variables, such as per capita reconstruction funds assigned by the government to

each village (Rossi 1993: 29-30). Via regression analysis, Rossi measures the effects of selected

independent variables upon selected dependent indicators of recovery, with the goal of

determining the relative effects of action and structural variables upon village recovery.

Rossis regressions, though limited in scope and arguably flawed, show that only so-

called structural variables had a measurable effect upon recovery outcomes. Rossi selects the

percentage of public and private reconstruction projects completed as a variable to measure

recovery. He then chooses two action variables for his regression. The first, a measure of

residents opinions about their mayors qualifications, seeks to gauge leadership effectiveness.

The second, a measure of residents perceptions about their fellow citizens propensities to take

legal action presumably to secure more resources for personal rebuilding, although Rossi does

not specify acts as a measurement of individual initiative. Finally, Rossi selects three

structural variables: institutional strength as measured by the number of public services in

each village, economic resources as measured by the number of lire per capita allocated to

each village for recovery, and political culture as determined by whether the mayors

leadership style was democratic or clientelistic (Rossi 1993: 35). The regression shows, on a

99% confidence interval, that the structural variables account for 26% of the variation in the


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dependent variable. The action variables, by contrast, do not explain significant additional

variation in the dependent variable (Rossi 1993).

Rossis undertaking is remarkably close to my own we both aim to explain the origins

of differences in recovery outcomes across disaster affected communities and his approach and

conclusions provide a number of insights. Rossis choices to identify dependent and independent

variables across cases, and to define his dependent variable as recovery as measured by the

percentage of buildings reconstructed, anticipate my own structuring of this thesis. His

identification of institutional strength and political culture as structural variables also

provides a valuable reminder that societal variables affecting neighborhood recovery in New

Orleans may well have been in place before the storm. Finally, his conclusion that action-

based variables such as leadership effectiveness did not affect recovery after the earthquake

provides a direct challenge to my attempt to explain neighborhood recovery through resident-

driven recovery initiatives.

Rossis focus on structural variables was likely informed by the work of

Haas, Kates, and Bowen, editors of the 1977 book Reconstruction Following Disaster, which

was the first substantial work to attempt to explain the process of disaster recovery.4 The authors

based their work on analysis and comparison of four cases: the recovery of San Francisco after

its 1906 earthquake and fire, the recovery of Anchorage after its 1964 earthquake, the recovery

of Rapid City, South Dakota after its 1972 flood and finally the recovery of Managua, Nicaragua

following its 1972 earthquake. Haas et al suggest that nature and rate of disaster recovery is

primarily governed by structural variables. They assert that [t]he reconstruction process is

ordered, knowable, and predictable(Haas, Kates et al. 1977: 262), and argues that much of the

4 The editors were able to find only four sources two of them unpublished that attempted to move beyondindividual case analysis and understand and explain recovery in broader terms Haas, J. E., R. W. Kates, et al., Eds.(1977). Reconstruction Following Disaster. Environmental Studies Series. Cambridge, Ma, MIT Press..


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pace of post-disaster recovery is determined by three variables: the extent of damage, the

available recovery resources, [and] the prevailing predisaster trends (Haas, Kates et al. 1977:

xxviii). They find prevailing economic and demographic trends to be of particular importance:

[W]e find strong evidence for acceleration of predisaster trends in recovery. Simply stated, rapidlygrowing cities recover rapidly; stable, stagnant or declining cities recover slowly and may even have theirdecline accelerated. (Haas, Kates et al. 1977: 19)

However, they also note that leadership, planning, and organization likely play roles in

determining the rate of recovery. While they acknowledge that this speculation is primarily

based on intuition or is anecdotes, they conjecture that leadership and planning spur recovery by

reducing uncertainty and thereby inspiring confidence, prompting populations to reinvest and

rebuild more quickly (Haas, Kates et al. 1977: 19-22).

Like Rossi, Haas et al provide valuable insights into variables that could be affecting the

rates of recovery in Broadmoor, Gentilly, and Lakeview. Although they take entire cities as their

units of analysis, the primary variables they identify degree of damage, available resources,

and pre-disaster trends certainly apply at the neighborhood level as well. Moreover, their

insight that leadership could affect rates of disaster recovery by increasing confidence among

populations that are otherwise hesitant to rebuild begs further investigation.

Adding to the list of variables that could be affecting residential recovery rates in

Broadmoor, Gentilly, and Lakeview, early research emerging from New Orleans suggests that

race, class, and homeowner status have profound effects on individuals recoveries. In a study

based on a Gallup poll of Katrina Survivors conducted one month after Katrina, Elliot and Pais

find that both race and class played important roles in determining survivors disaster

experiences and post-disaster life situations. Both variables were critical, the authors found;

neither [could] be readily reduced to the other (Elliott and Pais 2006: 317).


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Of particular interest to this thesis were the authors findings about the effects of race and

class on variables that would help individuals and families to return to the city and rebuild their

lives. Overall, the study indicated that race played a significant role in determining individuals

emotional stress and degree of social support after the storm, that class was an important

determinant of individuals post-storm access to their homes and their intentions to return to the

city, and that both variables were significant predictors of individuals access to their pre-storm

jobs (Elliott and Pais 2006: 305-316). The findings have profound significance for neighborhood

recovery in the wake of Katrina, as geographical segregation by race and class is widespread in

New Orleans.

The authors found that another demographic variable homeowner status was also

having a marked affect on resident return.

75% of all homeowners who reported their properties as damaged but still livable had already returnedto them one month after the storm. Among renters, the same return rate was less than 25%....this lowerrate may reflect not only lower attachment to place among renters and boarders but also less power overdecisions about whether to re-enter and or re-develop damaged properties. (Elliott and Pais 2006: 309)

Thus, neighborhoods with a higher portion of renters might well be expected to experience

slower or less complete recoveries. Indeed, in the two and a half years since Katrina, landlords

flood-affected neighborhoods with high portions of rental properties, like the 7th Ward, have

been selling their rental properties to the states Louisiana Recovery Authority through The Road

Home program, and then re-investing those funds in properties elsewhere (Cynthia Hedge

Morrell, August 1, 2007).

Class and homeowner status also interact in their effects on resident return. The authors

found that income as an isolated variable was correlated with intention to return, with richer

residents slightly more likely to plan to return to the city than poorer residents (Elliott and Pais


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2006: 316). Their most important finding, however, concerned the relationship between income

and intention to return among homeowners:

Generally speaking, we would expect these two indicators of class resources [home ownership andincome] to point in the same direction, but here they do not. Instead, they indicate that lower-income

homeowners are more likely to report plans to return to their pre-Katrina communities than higher-income homeowners, both of whom are more likely to report plans to return than renters. (Elliott and Pais2006: 315)

Wealthier homeowners are less likely to be tied to their properties with restrictive mortgages, the

authors point out, and also have greater access to the financial resources that facilitate a move.

Their finding suggests that both relatively wealthy and relatively poor flooded neighborhoods

might have a significantly more difficult time recovering from post-Katrina flooding than

working-class neighborhoods with high rates of home ownership.

Race-based variation in access to employment also has significant implications for

neighborhood recovery in New Orleans, given racial segregation in the city. The authors

findings were stark. [A]ll else equal, black workers from New Orleans were 3.8 times more

likely to report having lost their pre-Katrina jobs than white workers (Elliott and Pais 2006: 315).

Moreover, within the population of black workers, those with pre-storm incomes between

$10,000 and $20,000 per year were twice as likely to have lost their jobs after Katrina as workers

with annual incomes between $40,000 and $50,000. The authors conclude that low income

blacks specifically not blacks or low-income workers generally have the most tenuous hold

on their jobs (Elliott and Pais 2006: 310). Access to employment can be an immediate draw

back to the city, (Hank, July 19, 2007) and eventual access to employment is also critical to the

long-term process of rebuilding ones home and restoring ones life (Will, June 14, 2007). Thus,

neighborhoods with a high portion of poor, black residents could be expected to be significantly

hindered in their recoveries because of employment prospects for their residents.


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Finally, the authors findings about racial variation in long-term optimism amongst New

Orleans residents could well have implications for neighborhood recovery. The authors reported

that race, not class, has a strong influence on post-disaster stress associated with Hurricane

Katrina, with blacks generally reporting higher stress levels than whites, all else equal (Elliott

and Pais 2006: 312). Moreover, the authors found that the largest difference between whites and

blacks occurred when respondents were asked to rate their stress when looking five years into the

future, with blacks significantly less optimistic about the long-term future than whites (Elliott

and Pais 2006: 312). While significant research has not been performed on the subject, many

who have been following the New Orleans recovery believe that individual residents optimism

whether grounded or groundless plays an important role in their decisions to return to the city

(Virginia Saussy, June 18, 2007). Thus, significantly lower levels of optimism about the future

among black residents could well be a further strike against predominantly black neighborhoods

in their attempts to recover. In sum, Elliott and Paiss findings suggest that race, class, and

homeowner status play a substantial role in individual-by-individual recovery.

The below list summarizes the individual context variables that the authors identify:

Individual Context Variable Authors

Institutional Strength / Available Public Services Rossi

Economic Resources Rossi, Haas

Overarching Political Culture Rossi

Pre-Disaster Economic and Development Trends Haas

Race Elliott

Class Elliott

Homeowner Status Elliott

Group Context Variables

Thus far, the studies I have considered focus upon variables that affect recovery on an

individual by individual basis. These variables affect community or citywide recovery when

they are aggregated over a population. They do not, however, directly account for the role that


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collective efforts can play in spurring recovery. Another body of literature exists, however, that

does consider why such movements emerge and what makes them effective. These studies

suggest an array of variables that can affect the emergence and success of such collective

recovery efforts, and given my ultimate argument that divergent recovery outcomes in

Broadmoor, Gentilly, and Lakeview are due to the success of resident-driven recovery efforts in

Broadmoor and Lakeview and the failure of Gentillys effort, these studies and the variables they

propose are important for my consideration.5

The first, a study of community recovery efforts in

California, demonstrates that recovery can hinge on a communitys internal capacity to respond

to the disaster, and suggests that community-based disaster responses are uniquely suited to drive

recovery because of their flexibility and local knowledge. The second, a study of recovery

efforts in the wake of Japans Kobe earthquake and Indias Gujarat earthquake, suggests that a

communitys pre-existing social capital and leadership capacity can be critical to its ability to

mount an effective response to a disaster in the first place. The third, a study of the recovery of

the process of two flooded Midwestern towns, illustrates that recovery outcomes depend on the

process by which decisions are made about recovery. The fourth and final study, which

examines neighborhood-driven development in non-disaster settings, suggests that community-

driven development efforts succeed if they arise from resident preferences, have adequate human

and monetary resources, form diverse arrays of supportive partnerships, and exist in creative

tension with city government. Insights from these articles are important because they demand

that my own research methodology be able to test their applicability in Broadmoor, Gentilly, and

Lakeview. Indeed, I argue in Chapter Four that these factors do a great deal to explain these

neighborhoods divergent recovery outcomes.

5 As in the last section, I provide a chart at the end of this section identifying these variables and the authors whopropose them.


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A study of community-based responses to Californias 1994 Northridge earthquake in

the low-income Ventura County towns of Piru and Fillmore conducted by Bolin and Stanford

suggests that especially in low-income communities, recovery can depend on a communitys

ability to mount an organized and internally-driven response to the devastation (Bolin and

Stanford 1998). The towns were less immediately resilient in the earthquakes wake than

surrounding communities not because they had sustained more physical damage, but rather

because their populations of poor recent immigrants were unable to cope with the losses and

burdens imposed by the disaster and recover on an individual level (Bolin and Stanford 1998:

23). Earthquake insurance, the authors point out, was limited to a minority of primarily higher-

income homeowners who lived in adjacent communities (Bolin and Stanford 1998:24). The

communities lack of initial resilience also stemmed from their high portions of recent Latino

immigrants who lacked knowledge about federal bureaucracy and their own legal entitlements

[and] were reluctant to avail themselves to public resources to assist in their disaster-related

needs (Bolin and Stanford 1998: 26). Thus, the poor immigrant populations of Fillmore and

Piru lacked the personal resources to recover, and were also unable to tap into well-established

recovery channels on an individual-by-individual level.

The authors report that innovative community-based recovery efforts were the means by

which these hurdles were overcome. Three local organizations, Affordable Communities in Piru,

along with Cabrillo Economic Development Corporation and Rebuild: Hand to Hand (also

known asMano a Mano) in Fillmore, worked to foster recovery in the two towns. They secured

substantial federal relief funds to assist with ongoing homeowner repair efforts, as well as to

build new affordable housing units (Bolin and Stanford 1998: 30-31). These community-based


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efforts, the authors report, helped to make up for the shortfall of relief that individuals in both

towns were receiving, and played an important role in fostering recovery in both towns:

The NGOs, by using local knowledge and expertise, and establishing progressive working relationshipswith the city, county, and federal agencies, were able to implement programs that connected victims with

unmet needs to a diversity of resources. By targeting poorer households that were not adequately servedby standard FEMA / SBA disaster programs, they were able to promote timely recovery. (Bolin andStanford 1998: 34).

The authors further assert that the locally-based nature of these groups was critical to their

success:

These community-based programmes have generally used local knowledge and capabilities and beenmore flexible and sensitive to local conditions than standard technocratic federal disaster-assistanceprogrammes are able to be. (Bolin and Stanford 1998: 22)

The cases of locally-driven redevelopment in Fillmore and Piru thus provide a precedent for the

potential of community-based disaster recovery efforts, showing that these efforts can utilize a

synergy of initiative, organization, and local knowledge to connect individuals with the resources

they need to recover.

The cases of Fillmore and Piru also suggest that local implementation capacity can be an

important variable the success of recovery efforts. For example, Bolin and Stanford report that

while theMano a Mano organization had important local contacts and legitimacy in the

community, its staff lacked the grant-writing skills of more experienced NGOs also working in

the area (Bolin and Stanford 1998: 32). As a result, much of its work was eventually taken over

by a local affiliate of Habitat for Humanity. The authors also note that an 81-unit affordable

housing development planned by the Carbillo Community Development Corporation as part of a

recovery strategy for Fillmores Hispanic community was stalled by city council members who

cited concerns about the developments social impact (Bolin and Stanford 1998: 32).

Carbillos size and grassroots nature may well have limited its potential to see the project

through, as it lacked the clout and wherewithal to secure even local political approval. Thus, the


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recovery experiences of Fillmore and Piru reveal both the potential and some of the possible

limits of community-based efforts to spur and foster recovery from a disaster. In subsequent

chapters, I argue that resident-driven efforts in Broadmoor and Lakeview have in many ways

overcome such limitations. The cases of Fillmore and Piru demand that I provide a compelling

explanation of how Broadmoor and Lakeview cleared these hurdles.

Bolin and Stanford highlight local knowledge and local implementation capacity as

important contributors to the success of collective recovery efforts, but what other variables play

a role? In their study of community-based earthquake recovery in Kobe, Japan, and Gujarat

State in India, Nakagawa and Shaw conclude that social capital and leadership capacity were

important determinants in communities abilities to mount successful internally-driven recovery

efforts (Nakagawa and Shaw 2004). They define social capital as a function of trust, social

norms, participation, and network[s] within communities (Nakagawa and Shaw 2004: 5). They

first examine the recovery experience of the Mano neighborhood in Kobe after that citys

devastating 1995 earthquake. Mano had not been designated by Kobes government as a

readjustment and redevelopment zone, so like neighborhoods today in New Orleans, a great

deal of homegrown initiative would be required for its recovery to be successful (Nakagawa and

Shaw 2004: 13). Unlike surrounding neighborhoods, Mano had a history of neighborhood

leadership and had developed a high degree of social capital as the authors define it. The

communitys first well-established leader arose in the 1960s and led the community in a drive to

curb pollution from surrounding factories, and by the time of the earthquake, a larger second

generation of leadership had taken his place (Nakagawa and Shaw 2004: 14). The neighborhood

also boasted an array of loosely-linked formal and informal organizations. Each block had its

own neighborhood association; womens, middle age, and elderly social clubs met regularly;


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neighborhood baseball teams competed against one another; a PTA kept close links between the

school and the neighborhood. All of these associations were themselves loosely connected

through the neighborhoods Machizukuri (Town Development) organization (Nakagawa and

Shaw 2004: 14).

Mano experienced a highly successful recovery, and the authors assert that the success

in Mano owes much to its peoples efforts, the web of community groups and local leadership

(Nakagawa and Shaw 2004: 14). During the neighborhoods recovery, Mano residents

constructed a neighborhood organization center, founded a Manokko (private limited

company) for community development, prepared housing proposals for the construction of low-

income housing for displaced residents, lobbied for elderly housing, and ran a daycare center

(Nakagawa and Shaw 2004: 13). The authors argue that the neighborhoods loosely connected

alliance of residents groups made it possible to plan and implement community development

projects or to conduct various activities quite flexibly and quickly, immediately after the

earthquake. The neighborhoods well-established leaders, they argue, also played a

fundamental role in crafting its comprehensive response to the quake (Nakagawa and Shaw

2004: 14).

The authors, after analyzing the social networks at play during Manos recovery,

identified three broad categories of social capital from which he neighborhood benefited. The

first, bonding social capital, held small communities and groups within the neighborhood

strongly together with bonds of trust and frequent contact. The second, bridging social capital,

held these tight communities loosely together to form the neighborhood, and also constituted the

bonds between the neighborhood and affiliated NGOs and universities. The third, linking social

capital, consisted of the formal collaboration between the neighborhood and government


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entities (Nakagawa and Shaw 2004: 15-16). All of these forms of social capital, the authors

asserted, had contributed to Manos singular success.

In Gujarat, as in Kobe, the authors found that social capital and leadership played a

substantial role in spurring recovery outcomes. They compared the experiences of four separate

jatis6in the city of Bhuj, which was at the epicenter of Gujarats major 2001 earthquake. Of

thesejatis, the Soni community had the lowest annual per capita income, yet it enjoyed the most

successful recovery rate (Nakagawa and Shaw 2004: 19). Via written surveys and interviews,

the authors concluded that the Sonijati scored the highest in each of the three social capital

categories that had been identified in the Kobe case (Nakagawa and Shaw 2004: 22). Members

of the Sonijati also reported the higher trust in their communitys leader than did members of

the three otherjatis in the study (Nakagawa and Shaw 2004: 23).

As the Mano and Soni community cases show, the authors conclude, even in the

challenging situation of rehabilitation, communities with social capital can perform well.

Moreover, they assert, strong leadership inside the community is also essential for any

collective action (Nakagawa and Shaw 2004: 23). Therefore, in assessing a communitys

ability to mount its own organized effort to recover from a disaster, both social capital and

leadership capacity are fundamental considerations.

The success of recovery efforts also depends upon the ways in which they are carried out.

In their study of a 1997 flood that devastated the towns of Grand Forks, North Dakota, and East

Grand Forks, Minnesota, for example, Kweit and Kweit found that recovery outcomes depended

on the process by which decisions about recovery are made. The study compares citizen

satisfaction with recovery outcomes across the two towns, and concludes that residents of East

Grand Forks were significantly more satisfied with their towns recovery than were residents of

6A Jati is essentially a caste, which in a local context functions as extended social organization and support network.


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If I am to successfully account for divergent recovery outcomes between Broadmoor, Gentilly,

and Lakeview by arguing that Broadmoor and Lakeview residents mounted more effective

recovery efforts than did Gentillys residents, I must therefore examine the roles that human and

monetary resources played in each neighborhoods effort. As I show, although all three

neighborhoods efforts had the involvement of college educated and technically adept residents,

only Broadmoor and Lakeview managed to secure substantial funding for their initiatives.

Petermans second criterion asserts that the most successful community development

initiatives are generated by and strongly supported by residents.

2. Community development must be demand driven, arising from grassroots community organizing.It cannot be legislated into existence by public officials, no matter how well intentioned.(Peterman 2000: 155-156)

This principle is of vital importance for a number of reasons. Of course, an initiative that

neighborhood residents do not like or fully support is undesirable in and of itself. Moreover,

community input into a projects goals will help to hone and target that projects effects within

the neighborhood, because residents know their neighborhood better than anyone else. More

fundamental, as Peterman points out, is the issue of community empowerment (Peterman

2000: 156). If residents are actively engaged in the work of a neighborhood development

project, that involvement builds their collective capacity to see more positive change through in

the future. This is the proverbial difference between giving a man a fish and teaching him to

fish. My research attempts to account for the importance of community development projects

being community-driven, and argues that resident involvement in the planning and

implementation of recovery initiatives was more central in Broadmoor and Lakeview than it was

in Gentilly.

Peterman also makes the important observation that neighborhood capacity to drive

development, while critical and often underutilized, is in itself insufficient:


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3. Community leaders must build and maintain strong and direct ties with public officials; technical,legal, and financial experts; and other community organizations and umbrella coalitions oforganizations. (Peterman 2000: 155)

Peterman argues that residents should retain core control of their neighborhoods development,

but that in order to be successful, they must develop a diverse network into which they can tap

for resources, expertise, and support. Taking this observation into account, my research shows

that Broadmoor and Lakeview developed a diverse array of partnerships that augmented

residents abilities to implement recovery themselves, whereas Gentillys partnerships did not

build residents implementation capacity.

Petermans final criterion argues that the relationship between neighborhoods and city

government that is most conducive to the success of neighborhood development efforts is

characterized by a degree of tension:

4. The relationships between the community and those governmental agencies that have interests inand responsibilities with respect to the community must be neither too friendly nor tooconfrontational. An atmosphere of creative tension appears most appropriate. (Peterman 2000:155)

This, according to Petersen, is because continued resident involvement and investment in

neighborhood development processes depends on residents not fully trusting their city, and not

expecting constructive work to get done without their continued involvement. Petersen cites an

example of a resident-led effort to enact full resident management of a Chicago Housing

Authority (CHA) development. The residents succeeded in their quest, having been forced to

cohere as an effective group and deepen their commitment in the face of a disorganized and

uncooperative CHA bureaucracy (Peterman 2000: 121-122). Resident management was going

well, until a new chairman arrived at CHA who was so enthusiastic about the residents work

that he invited them to work more closely with the Authority:

As the resident leaders began to rely more on the friendly officials at the CHA[o]ne by one, their linksto the external community were severed, and they came to be seen more as an arm of the CHA than anindependent corporation. Over time, the resident management effort stalled and ultimately failed.(Peterman 2000: 156)


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The creative tension Petersen describes is an important and not immediately obvious

consideration when evaluating the causes of the success or failure of neighborhood-driven

recovery efforts in New Orleans. As I argue in subsequent chapters, the success of efforts in

Broadmoor and Lakeview was predicated upon residents low expectations for and distrust of

city government, whereas part of the failure of Gentillys effort stemmed from its trust of and

over reliance on various governmental entities.

To summarize the variables that authors propose affect the emergence and effectiveness

of collectively-driven recovery efforts, I present the below chart:

Group Context Variable: Authors

Recovery efforts draw on local knowledge Bolin, Peterman

Residents control recovery planning and implementation Bolin, Kweit, Peterman

Efforts develop sound implementation capacity Bolin

Affected community has established leadership Nakagawa

Affected community has high internal social capital Nakagawa

Efforts utilize outside ties and resources Nakagawa, Peterman

Efforts maintain "creative tension" with government Peterman

***

My overarching goal in this thesis is to account for a difference in outcome between

neighborhoods: explaining why Broadmoor and Lakeview are recovering consistently while

Gentilly is not. Thus far, I have presented a number of studies that present potential explanations

for this difference in outcome. These, as we have seen, range from factors that enable or inhibit

recovery on an individual-by-individual basis, such as the demographics of the affected

population and level of destruction suffered, to variables that determine the success or failure of

the concerted recovery efforts mounted in the disasters wake, such as the pre-existing leadership

capacity on which they are based or their success at forming constructive outside partnerships.

My thesis must account for this range of variables in its explanation of the divergent recovery

outcomes in Broadmoor, Gentilly, and Lakeview.


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II. Methodology

In the remainder of this chapter, I argue that my chosen methodology a comparative analysis of

the recovery experiences of Broadmoor, Gentilly, and Lakeview based on interviews, participant

observation, repopulation data, and demographic information provides the best means by

which to isolate the causes of the difference between Broadmoors and Lakeviews consistent

recoveries on the one hand and Gentillys inconsistent recovery on the other. I also argue that

my choice to compare Broadmoor, Gentilly, and Lakeview is itself optimal, because while the

neighborhoods are fundamentally similar enough to warrant comparison, the differences between

them allow for a great number of variables that potentially explain their divergent recovery

outcomes to be tested.

Comparative Analysis of Broadmoor, Gentilly, and Lakeview

My thesis utilizes a qualitative comparative research methodology, which provides the best

research framework for explaining this difference between cases. As Ragin explains,

comparative researchers examine patterns of similarities and differences across cases and try to

come to terms with their diversity (Ragin 1994: 107). After developing in-depth and

multifaceted qualitative understandings of each of the cases in question, comparative researchers

use rigorous logical analysis to pinpoint potential causes of differences in outcome between the

cases. Scholars of revolutions, such as Theda Skocpol (Skocpol 1979) and Timothy Wickham-

Crowly (Wickham-Crowley 1992), have used comparative methodology to provide convincing

explanations of why certain revolutionary movements succeed and others fail. Their

methodology allows for accounts that are qualitatively rich and multifaceted but also rigorous,

logical and convincing, striking what Ragin calls the balance between discourse on cases and

discourse on variables that characterizes good comparative social science (Ragin 1991: 1).


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Comparative methodology is particularly suited to the study of neighborhood recovery

outcomes in New Orleans because it allows for this balance. A qualitative study that sought only

to capture the lived experience of resident return in New Orleans could shed a great deal of light

on the processes by which residents have organized around their neighborhoods in the storms

wake. However, this exposition alone would provide a relatively weak basis upon which to

explain divergent rates of neighborhood recovery. Conversely, a well conceived and executed

statistical study of the causes of neighborhood residential recovery could well isolate variables

that have statistically significant correlations with rates of resident return across neighborhoods.

However, if it found a particular resident organizing variable to be statistically significant, it

alone could do little to flesh out how and why residents successfully organized to produce this

outcome. Comparative methodology, by contrast, allows for sound qualitative analysis of each

neighborhoods recovery experience and also for logical explanatory analysis to account for why

certain neighborhoods in New Orleans are experiencing more consistent residential recoveries

than others.

An explanation of my choice of Broadmoor, Gentilly, and Lakeview as units of

comparison sheds light about the logical systems of analysis that comparative methodology

employs. While the comparative method aims to explain differences between cases for

example why Broadmoor and Lakeview are experiencing consistent residential recoveries but

Gentilly is not its cases must be similar enough to warrant the comparison between them

(Ragin 1994: 105-107). Broadmoor, Gentilly, and Lakeview are indeed sufficiently alike to

deserve comparison. All three are primarily residential neighborhoods comprised of single

family homes and duplexes (or doubles as they are known in New Orleans). All three were

badly flooded in the wake of Katrina, with their housing stocks so damaged that the vast majority


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(>80%) of residents were displaced from their homes for at least six months as they undertook

repairs.7

In all three neighborhoods, the majority of residents owned their houses, meaning that

most residents had direct control over whether to rebuild houses and return. Discourse took

place after the storm among residents, planners, politicians, and the media about whether any of

these three neighborhoods should be rebuilt.8

Thus, Broadmoor, Gentilly, and Lakeview

residents all faced great uncertainty about their neighborhoods futures, and recovery in each of

the neighborhoods would require that this uncertainty be overcome on an individual-by-

individual basis as residents decided to return. Finally, each neighborhood saw the emergence of

an organized recovery effort by its residents. It is on the basis of these fundamental similarities,

summarized by the chart below, that I undertake this comparative study of the recoveries of

Broadmoor, Gentilly, and Lakeview.

Variable Broadmoor Gentilly Lakeview

Primarily residential Yes Yes Yes

Over 50% of households resident-owned Yes Yes Yes

Housing: single family homes and duplexes Yes Yes Yes

Badly flooded Yes Yes YesMost residents experience 6+ month

displacement Yes Yes YesDiscourse questions neighborhood return Yes Yes Yes

Resident-driven recovery efforts present Yes Yes Yes

Comparative studies use simple Boolean logic to hone in on potential explanations for the

difference between their cases.9

Broadmoor, Gentilly, and Lakeview are ideally suited to a

comparative analysis, as they differ in many ways that literature suggests should affect their rates

7

Figures on early rates of resident return for the three neighborhoods are not available, but by most accounts, thetotal returned population in all three neighborhoods was still in the high single digits or very low teens in Februaryof 2006 (Virginia Saussy, June 18, 2007; Jack Stenson, July 9, 2007; Jennifer Campbell, July 18, 2007).8 For example, although it was never acted upon, the Bring New Orleans Back commission plan designatedBroadmoor, Gentilly, and Lakeview as Neighborhood Planning Areas, recommending a four month moratoriumon building permits in the neighborhoods until a firm decision had been reached about whether or not to rebuildthem. BNOB, U. P. C.-. (2006). Urban Planning Committee: Action Plan for New Orleans Executive Summary.9 John Stewart Mill coined the terms method of agreement and method of difference to describe the process.For more on Mills method of similarity and Mills method of difference, see Little Little, D. (1991). Varieties ofsocial explanation : an introduction to the philosophy of social science. Boulder, Westview Press..


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of recovery. For example, Lakeview is a predominantly middle- to upper-middle class

neighborhood, whereas Gentilly and Broadmoor residents are on average less well off.

Likewise, Broadmoor and Gentilly have substantial African American populations, while

Lakeview is primarily white. Broadmoor and Lakeview had established residents associations

prior to Katrina, whereas Gentilly did not.10

These and many other differences between the

neighborhoods are further explored in Chapter 2, but it is important to note for now that these

differences allow for logical inferences to be drawn about the causes of recovery outcomes in the

three neighborhoods. For example, although we have seen that both Haas et al and Elliott and

Pais stress the importance of individual access to financial resources in recovery, the fact that

both Broadmoor and Lakeview are experiencing consistent residential recoveries in spite of their

widely divergent average incomes suggests that average resident income provides an insufficient

explanation for consistent residential recovery. Similarly, neither neighborhood racial makeup

nor the percentage of residents living in poverty explains differences between the

neighborhoods residential recovery outcomes. Conversely, the fact that both Broadmoor and

Lakeview had residents associations before the storm, but Gentilly did not, could help to

account for Broadmoors and Lakeviews relative recovery success.

Variable Broadmoor Gentilly Lakeview

Dependent Variable:

Residential recovery Consistent Inconsistent Consistent

Independent Variables:

Average Income*

$36,400 $46,000 $64,000

% in Poverty* 32% 15% 6.60%

% African American* 68% 68% 1.30%

Residents association existed before the storm Yes No Yes

10 Some individual neighborhoods within Gentilly were served by residents associations prior to the storm, but noorganization served the area as a whole before the founding of the Gentilly Civic Improvement Association after thestorm.* GNOCDC (2008). Pre-Katrina Data.


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On its own, Boolean analysis of this type is most effective at dismissing potential causes

of the difference in question. It can also be used, as I just did in the case of the presence or

absence of residents associations, to suggest possible explanations for the difference. Of course,

once an explanation is suggested, qualitative follow-up is required in order to determine whether

it bears fruit. For example, any conclusion that the preexistence of residents associations in

Broadmoor and Lakeview contributed to their consistent recoveries would need to be based on

in-depth qualitative analysis of what these residents associations actually did before and after

the storm. Thus, Boolean logic can eliminate some explanations and suggest others, but it is

certainly a limited tool.

Nonetheless, the role of Boolean analysis in this thesis is not constrained to simply

eliminating possible explanations of Broadmoors and Lakeviews consistent housing recoveries.

It is also be used to hone in on an explanation of how and why resident-driven recovery efforts in

Broadmoor and Lakeview have maintained high levels of resident engagement and implemented

a substantial number of successful recovery initiatives while Gentillys has not. Indeed, it is

notable that all three of the neighborhoods I have chosen to compare have concerted resident-

driven recovery efforts present, because on a basic level, Boolean logic would suggest that the

best way to test the effect of resident-driven efforts on recovery would be to compare

neighborhoods where efforts were underway and neighborhoods where no efforts were present.

However, given constraints of research time and writing scope, it was much more fruitful and

useful to compare two neighborhoods with successful resident-driven efforts and one

neighborhood with an unsuccessful effort. The most relevant information for disaster-stricken

communities is not only whetherresident-driven efforts can have tangible effects upon recovery,

but also how and why these efforts succeed, and this information is most effectively gathered by


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comparing successful efforts and failed efforts. The comparison of two successful efforts helps

to identify their core unifying components, and the comparison of these two efforts to Gentillys

unsuccessful effort helps to pinpoint potential pitfalls that future efforts would be well advised to

avoid.

Interview and Participant Observation-Based Research

A combination of interviews, primary source reading, and participant observation

comprised the bulk of the research performed for this thesis, and these techniques proved to be

ideally suited to the task at hand. Efforts within the three neighborhoods are still ongoing, and

with the exception of one report on Broadmoors planning process (Hummel 2007), these efforts

have not been extensively documented. Thus, the best way for me to learn about these efforts

was to immerse myself in them.

Before I arrived in New Orleans, I contacted the president of each neighborhoods

residents association and gained each individuals approval to conduct the research. These

individuals were among the first people I interviewed in each neighborhood, and their contacts

(along with the legitimacy they lent me) allowed me to effectively snowball out into the

neighborhoods. I also placed an advertisement explaining my research in The Trumpet, a local

recovery-centered newspaper, which generated a substantial number of resident interviews. This

ensured that not all of my subjects were closely tied to the social networks of the recovery

organizations. Many of the residents I interviewed had not moved back into their homes and

were internally displaced within greater New Orleans. Through residents I met and through the

advertisement I placed in the Trumpet, I also secured interviews with residents who no longer

lived in New Orleans, whether by necessity or by choice. I performed fifty-six interviews in


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total: eighteen with Broadmoor residents, seventeen with Lakeview residents, and twenty two

with Gentilly residents.

I also sought, whenever possible, to take active part in the daily work of recovery. I

distributed fliers door-to-door, signed up children for a charter school, attended fundraising

sessions with Fortune 500 executives, moved doors and drywall, helped residents with their

Road Home applications, and sat in on as many neighborhood meetings as I could. This

participant observation gave me firsthand insight into the daily realities and challenges of

recovery, and gave me key insights that mere interviews would not have provided. Sitting in on

neighborhood meetings, for example, gave me a window on group dynamics and organizational

effectiveness that I could not have gained through one-on-one interviews.

Additionally, I consulted a variety of primary written sources from the three

neighborhoods. The most fruitful of these were recovery plans created residents of each of the

neighborhoods, as well as the Gentilly After Katrina listserv, a Yahoo email list started by

Gentilly residents after the storm. The plans provided valuable insights into each communitys

ultimate redevelopment goals, and also into the strategies by which each planned to attain these

goals. Membership on the Gentilly After Katrina listserv gave me access to all of the lists

archived emails, which provided valuable information about Gentillys gradual mobilization

after the storm.

***

In sum, literature on disaster recovery suggests a variety of variables that could explain the

different rates of recovery between Broadmoor, Gentilly, and Lakeview. My comparative

methodology and on-the-ground research allow me to test a number of these variables, and also

to explore the root causes of the neighborhoods divergent recoveries in-depth.


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Chapter 2: Neighborhood Comparison

In the last chapter, I highlighted a number of variables that affect recovery according to

disaster and community development literature. In this chapter, I examine the roles that a

number of these variables are playing in the recoveries of Broadmoor, Gentilly, and Lakeview, in

an attempt to isolate a variable that explains their divergent recovery outcomes. Through this

analysis, I argue that structural factors, such as the degree of damage each neighborhood

suffered, residents average pre-storm incomes, and neighborhood racial makeup, provide an

insufficient explanation of why Broadmoor and Lakeview are experiencing steady residential

recoveries but Gentilly is not. I use my analysis to argue that this difference could instead be

explained by the success of resident-driven recovery efforts in Broadmoor and Lakeview at

maintaining high levels of resident involvement and implementing an array of recovery

initiatives, versus the failure of Gentillys effort to do the same things. I substantiate this

argument in the subsequent chapter.

First, though, in order to provide a basis for my analysis and arguments, I introduce each

neighborhood, and show that Broadmoor and Lakeview have experienced spatially and

temporally consistent recoveries in Katrinas wake, while Gentillys has been inconsistent.

I. Introducing Broadmoor, Gentilly, and Lakeview

The three neighborhoods I examine in this thesis are primarily residential, comprised

mainly of single family homes and duplexes, or doubles as theyre widely known within the

city. Gentilly and Lakeview also have areas of commercial development that are struggling to

return in the storms wake, but these comprise a small fraction of the neighborhoods built

environments. As a result, the most fundamental aspect of recovery in each of these


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neighborhoods is the return of residents and the repair of homes. The recovery process in

Broadmoor, Gentilly, and Lakeview occurs one household at a time, and this fundamental

similarity11 allows for a direct comparison of their respective recovery efforts.

Broadmoor

Broadmoor is located in a shallow topographical bowl in the center of the city,

surrounded by the affluent Uptown neighborhoods of Audubon and Maryville / Fountainbleau

to its west and southwest, a smattering of poorer neighborhoods adjoining Central City to its

east and southeast, and an area of light industry to its north. It is itself a product of the

confluence of these neighborhoods, and as a result is quite diverse. It had 7,232 residents at the

time of the 2000 census, and its racial demographics very closely matched those of the city as a

whole (GNOCDC). The neighborhood is trisected by three roads, Napoleon Avenue,

Fountainbleau Drive, and Broad Street, which divide Broadmoor into three geographically and

demographically distinct segments. In the wake of Katrina, these areas have been designated

Subsection A, Subsection B, and Subsection C by the Broadmoor Improvement

Association. Subsection C adjoins the more affluent Uptown neighborhoods that surround

Tulane University, and it is the most affluent and most predominantly white of the subsections.

Subsection B, by contrast, is primarily African American, and many of its residents are quite

poor. Subsection A lies between the two on the demographics scale. The below map shows

Broadmoor and its three subsections:

11 Along with the other similarities outlined in the previous chapters methodology section.


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Before the storm, Broadmoor was served by a small but active residents association

known as the Broadmoor Improvement Association, or BIA. In the decade before the storm,

BIA leadership successfully advocated for new streetlights for the neighborhood, lobbied the

Corps of Engineers to undertake a multi-million dollar drainage project to help reduce flooding

in the neighborhood during rainstorms, and prevented the opening of a convenience store that

residents found undesirable (Bert Milton, June 13, 2007). Despite this activity, most residents

were not involved with the BIA prior to the storm.

Gentilly

Gentilly is a large and diverse area of New Orleans bordering Lake Pontchartrain. To

call it a neighborhood is slightly misleading, as it consists of twenty-one individual

neighborhoods with relatively distinct borders and demographics. The below map shows the

boarders of each of Gentillys neighborhoods:


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Gentillys pre-Katrina population, as of the 2000 census, was 43,863 residents (GNOCDC

2008).12 Gentilly was racially and socioeconomically diverse prior to the storm. Though most

of its individual neighborhoods reflected this diversity prior to Katrina, some, such as the Lake

Oaks neighborhood, were substantially wealthier than average. Others, such as the historically

black Pontchartrain Park neighborhood, were substantially more racially homogenous.

Generally, Gentilly was known as the home of the working middle class backbone of the city.

One resident explained that We have a lot of university professors and high school teachers

living in Gentilly. We had a very healthy amount of first responders. Nurses. Professionals like

that (Simon Wright, June 23, 2007).

Although the bulk of Gentilly consists of residential neighborhoods, it is also a home to

large commercial areas, most notably a development at the intersection of Gentilly Boulevard

and Elysian Fields Avenue, along with strip shopping and a small mall at the eastern edge of

Gentilly along the Chef Menteur Highway. Gentilly is also home to four universities: The

12 The Greater New Orleans Community Data Center website splits Gentilly into eight smaller subsections, and doesnot present aggregate data for Gentilly as a whole. As a result, I have manually aggregated the Gentilly-wide data Ipresent in this thesis.


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University of New Orleans, Southern University of New Orleans, Dillard University, and a

Baptist theological seminary.

Several neighborhoods within Gentilly had residents associations prior to the storm. The

largest and most active of these was the Pontilly organization, which served the Pontchartrain

Park and Gentilly Woods neighborhoods (Adrian James, July 26, 2007). Gentilly as a whole,

however, did not have an overarching residents association.

Lakeview

Lakeview is an almost entirely residential neighborhood that lies in between the Orleans

Avenue Canal and the 17th Street Canal. As one resident told me, Lakeview was the last bastion

of white middle class in the City of New Orleans (Harry Stevenson, June 29, 2007). Though

large, with a population of 17,507 at the time of the 2000 census (GNOCDC 2008),13

the

neighborhood was quite tight knit. Many residents with whom I spoke credited neighborhood

institutions, such as the Lakeview Civic Improvement Association, St. Dominics Catholic

Church, St. Pauls Episcopal Church, and the grocery store, Lakeview Fine Foods, with

cementing a sense of common neighborhood identity prior to the storm. On Lakeviews sense of

community, one woman remarked: Its almost to the point where, you know the Andy Griffith

show, with Mayberry USA? You walk down the street, everybody waved, everybody was

friendly, it was nice. You might not know everybody by name, but you know their face (Sarah

Farmer, July 2, 2007). The below map shows Lakeviews borders:

13 The Greater New Orleans Community Data Center splits the area that residents know as Lakeview into threeseparate areas: West End, Lakeview, and Navarre. These are the three areas served by the Lakeview CivicImprovement Association. Consequently, I have manually aggregated data from these three neighborhoods to arriveat composite figures for Lakeview, as residents and the Lakeview Civic Improvement Association define it.


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Lakeview bred a degree of loyalty amongst its residents that outsiders often found

surprising. Real Estate agents working in the neighborhood joked with potential buyers that if

you buy in Lakeview, you die in Lakeview (Jennifer Campbell, July 18, 2007). Children who

had grown up in the neighborhood moved back in droves. Several residents reported instances of

three generations of a family living in close proximity to one another in Lakeview, and one man

bragged Ive got four generations within a two block area of my house (Phillip, July 13, 2007).

Lakeview was served by a large, well organized, and very active residents association

prior to Katrina known as the Lakeview Civic Improvement Association, or LCIA. The LCIA

served in many ways as a small town government, striving to maintain suburban living standards

within Lakeviews borders. In an agreement with the state of Louisiana, it arranged for extra

taxes to be levied on Lakeview residents to support a supplementary police force for the

neighborhood. Dissatisfied with city services, it also investigated the possibility of creating

quasi-governmental agencies to take care of streets, drainage, [and] water for the neighborhood

(Jennifer, July 18, 2008). During the 1980s, it even led an unsuccessful attempt to secede from

Orleans Parish and incorporate itself as its own city.


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Katrinas Effects

Broadmoor, Gentilly, and Lakeview were all badly affected by the substantial flooding

that followed Hurricane Katrina. The map below shows the depth of water that affected each

neighborhood. Much of Broadmoor was submerged in eight or more feet of water, and

substantial portions of Lakeview and Gentilly were under ten feet of water or more. The

stagnant and often toxic water remained in the city for weeks, rendering most houses in the

neighborhoods uninhabitable.

Some houses, especially those that were close to levee breaches in Lakeview and Gentilly and

had been exposed to the tremendous forces of fast-flowing water, were structurally unsound and

had to be demolished. Most others remained structurally intact, but needed to be gutted

cleared of destroyed contents, muddy carpet, moldy dry

neighborhood recovery in new orleans

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