Sun, sea, sand and tsunami examiningdisaster vulnerability .docx

Sun, sea, sand and tsunami: examining
disaster vulnerability in the tourism
community of Khao Lak, Thailand
Emma Calgaro1 and Kate Lloyd2
1Department of Human Geography, Macquarie University,
Sydney, Australia and Stockholm Environment
Institute – Asia Centre, Bangkok, Thailand
2Department of Human Geography, Macquarie University,
Sydney, Australia
Correspondence: Emma Calgaro (email: [email protected])
The impact of the 2004 Indian Ocean tsunami on coastal tourism
communities highlights the
vulnerability of tourism destinations to external shocks. Based
on fieldwork conducted in Thailand
in the wake of this disaster, this paper addresses one
fundamental question: what sociopolitical and
environmental conditions contributed to the vulnerability of the
affected tourism community of
Khao Lak in the southern Phang Nga Province. We argue that an
understanding of the root causes
of destination vulnerability is vital not only for the successful

implementation of regional recovery
plans, but also for building long-term resilience against future
shocks. In the absence of an appro-
priate tourism vulnerability framework, this paper analyzes
Khao Lak’s vulnerability through an
innovative theoretical framework comprised of the
sustainability vulnerability framework, rela-
tional scale and place. The findings reveal that Khao Lak’s
vulnerability is shaped by 13 interlinked
factors. These are the complex outcomes of social norms and
developmental and dynamic gover-
nance processes driven by the competing agendas and scaled
actions of key government and industry
stakeholders. The identification and understanding of the
drivers of Khao Lak’s vulnerability and a
strong vulnerability framework have significant implications for
the wider tourism community. First,
the empirical findings provide tourism communities with a
blueprint for understanding the foun-
dations of their vulnerability to external shocks. Second, the
tourism vulnerability framework
presented here provides destination communities and
government stakeholders with an analytical
tool through which to analyze their unique sociopolitical

conditions. Together, these empirical and
theoretical contributions bring us closer to securing sustainable
livelihood futures for tourism
dependent communities.
Keywords: coastal hazards, place, relational scale, sustainable
development, tourism, vulnerability
assessment
Introduction
The World Tourism Organization (WTO) and nongovernment
organizations (NGOs)
such as Tourism Concern and the Netherlands Development
Programme have endorsed
tourism as having the capacity to stimulate development,
economic growth, new oppor-
tunities for poverty alleviation and self-governance, particularly
in regions that are
resource-scarce and have limited livelihood options. (Ashley et
al., 2000; WTO, 2005a).
Such endorsements have enticed many developing countries to
embrace tourism as a
viable livelihood alternative where fragmented small
economies, limited natural
resources (Wilkinson, 1989) and unequal terms of trade (Oliver-
Smith, 1996; Bankoff,
2003) limit livelihood options. This development trend has seen
tourism eclipse tradi-
tional subsistence-based livelihoods such as agriculture and
fishing as the main source
of revenue (Richter, 1993; UNEP, 2002).

Missing from the WTO’s advocacy of tourism’s developmental
capabilities is an
acknowledgement of the inherent vulnerability of host
communities to shocks, as was
doi:10.1111/j.1467-9493.2008.00335.x
Singapore Journal of Tropical Geography 29 (2008) 288–306
© 2008 The Authors
Journal compilation © 2008 Department of Geography, National
University of Singapore and Blackwell Publishing Asia Pty Ltd
mailto:[email protected]
powerfully demonstrated by the impacts of the 2004 Indian
Ocean tsunami. The reper-
cussions of prior events such as the 1997–1998 Asian financial
crises, the Bali bombings
of 2001 and 2005, the severe acute respiratory syndrome and
bird flu epidemics of 2003
and 2004 had already highlighted the sensitivity of destination
communities to both
localized and remote events beyond their control (Ritchie,
2004).
In the light of this, we deem it essential to investigate how
long-term benefits from
tourism can be sustained in the face of risk and vulnerability by
incorporating an
assessment of a host community’s vulnerability into all tourism
development and
management strategies. Research on risk and sustainability
supports this view: long-

term resilience plans aimed at securing future sustainable
livelihoods cannot be opera-
tionalized without an understanding of the underlying
sociopolitical processes and
environmental linkages that underpin vulnerability (Clark et al.,
2000; Cutter et al.,
2000; Pelling, 2003; Turner et al., 2003; Thomalla et al., 2006).
The tourism literature identifies five factors that help to explain
why some
destinations are vulnerable to shocks: the place-specific nature
of tourist activity
(Richter & Waugh, 1986, Sönmez et al., 1999), the fragility of
destination images
to negative perceptions of risk (Richter & Waugh, 1986;
Sönmez & Graefe, 1998;
Mansfeld, 1999; Huan et al., 2004), a high dependency on
tourism as a primary live-
lihood (Knox & Marston, 2004; Ritchie, 2004), a heavy reliance
on the marketing
strategies of international tour operators (Knox & Marston,
2004), and high levels of
seasonality (Méheaux & Parker, 2006). These are common
characteristics of tourism
activity in many developing country destinations including
those affected by the 2004
tsunami, in Thailand, Sri Lanka and the Maldives. The growing
popularity of using
tourism as a development tool in resource-scarce regions will
likely see this vulner-
ability increase (Knox & Marston, 2004). Seasonal tourism
flows and annual business
revenue can easily be disrupted by shocks, causing simultaneous
losses for household,
community, regional and national actors. Losses further
diminish investment confi-

dence, lower rates of job creation, slow economic growth and
reduce gross domestic
product (GDP) (Sönmez et al., 1999; Gurtner, 2004). Richter
and Waugh (1986)
observe that if there is trouble in one area tourists simply
choose alternate destina-
tions, which demonstrates the most disempowering
characteristic of tourism-
dependence for destination households and communities. In
contrast, international
tour operators and national governments anxious to retain
projected levels of GDP
and foreign exchange can avoid this pitfall by diverting
business to alternate
in-country or regional destinations.
While the identification of these provide significant insights
into the vulnerability of
tourism communities, a systematic analysis of the place-specific
environmental and
sociopolitical causal factors underlying vulnerability in tourism
destinations is missing.
This research addresses this omission by focusing on the
impacts of the 2004 tsunami
on Khao Lak, Phang Nga Province, southern Thailand. By so
doing, it provides the
foundational knowledge necessary for tourism community
stakeholders, regional plan-
ners and policy makers to formulate robust resilience building
strategies that account
for the root causes of destination vulnerability rather than the
consequences of shocks
alone.
Building a framework for analyzing tourism destination
vulnerability

Adopting an interdisciplinary approach, vulnerability is
recognized as a multidimen-
sional product of the coupled human–environment system and
defined as:
Examining disaster vulnerability, Thailand 289
The degree to which an exposure unit [human groups,
ecosystems and communities] is
susceptible to harm due to exposure to a perturbation or stress,
and the ability (or lack thereof)
of the exposure unit to cope, recover, or fundamentally adapt
(become a new system or
become extinct) (Kasperson et al., 2002: 7).
The vulnerability of a community or group is determined by
three dynamic and inter-
connected dimensions: exposure, sensitivity, and resilience
(Clark et al., 2000; Turner
et al., 2003). Exposure, a product of physical location and the
character of the built and
natural environment (Pelling, 2003: 48), is defined as the degree
to which an exposure
unit comes into contact with stressors or shocks (Clark et al.,
2000: 2). Sensitivity is
defined as the degree to which an exposure unit is affected by
any set of stresses (Clark
et al., 2000) and reflects the capacity of individuals or groups to
anticipate and with-
stand the impacts of a hazard (Pelling, 2003: 48). Sensitivity is

characterised predomi-
nantly by preexisting conditions of the social system that may
be improved or
exacerbated by coping and adaptation strategies post-shock.
Resilience is defined as the
ability of an exposure unit to absorb and adapt to recurrent
external stresses without
losing its fundamental structure and function (Adger et al.,
2002). Resilience is a direct
expression of the strength of the coupled human–environment
system reflecting its self
organization, learning, and adaptation capabilities in response
to shocks (Carpenter
et al., 2001).
The ability to anticipate, withstand, and recover from shocks
hinges upon people’s
access and entitlements to natural, economic, social and
political capital. These, in turn,
are determined by the strength and effectiveness of the
governance systems and social
networks (Hewitt, 1997; Adger, 2003) that facilitate (or
constrain) access to capital and
the competing agendas and ideologies driving them (Adger,
1999; Pelling, 2003; Wisner
et al., 2004). These are expressed through formal government
structures, political ide-
ologies, ethnicity, class, religion and social norms determined
by human agency and
wider historically embedded and contemporary sociopolitical
and economic processes
operating simultaneously at multiple scales of social
organization (Kelly & Adger, 2000;
Bankoff, 2003; Wisner et al., 2004). An awareness of the
processes that drive the uneven
distribution of power and resources within the social system is

therefore crucial to
understanding vulnerability.
Climate change, disaster management and food security research
has provided
numerous frameworks and methods for assessing vulnerability
in risk prone locations
(see Cannon et al., 2003), but none of these approaches have
been adapted to assess
vulnerability in tourism destinations. Nankervis (2000) does
provide an industry specific
vulnerability framework but its focus on all tourism business
stakeholders operating at
the global to local scales leaves the framework lacking
necessary detail at the commu-
nity level. In the absence of a suitable framework, this paper
presents a robust tourism
vulnerability framework consisting of three complementary
theoretical constructs:
Turner et al.’s (2003) sustainability vulnerability framework,
relational scale and place.
Together, these theoretical tools create a strong framework for
analyzing the multiple
causal factors and underlying power discourses that contribute
to the vulnerability of
tourism communities.
The sustainability vulnerability framework
Born out of the interdisciplinary systems approach to
vulnerability analysis, Turner et al.
(2003) present a framework that systematically identifies and
maps the scaled inter-
linked components and processes that heighten vulnerability
within the human–
290 Emma Calgaro and Kate Lloyd

environment system. Turner et al.’s (2003) sustainability
vulnerability framework was
chosen to guide and structure the analysis of destination
vulnerability based on its
inclusion of the multiple attributes of vulnerability. It captures
the dynamic and differ-
ential nature of vulnerability whereby populations,
characteristics and driving forces of
vulnerability change over space and time (Vogel & O’Brien,
2004). The framework not
only recognises that an individual’s or group’s exposure,
sensitivity and resilience to
shocks is directly linked to access and entitlements to resources
in a given location
(Figure 1) but also places this experience within a wider
context. The focus of the
framework expands to show the way in which resource
entitlements, distribution and
usage is influenced by evolutionary (Cutter et al., 2000;
Bankoff, 2003) sociopolitical
and environmental processes operating at multiple scales of
social organisation
(Figure 2). Further, the framework also shows that vulnerability
is affected by multiple
and compounding stressors and a population’s capacity to
respond and adapt over time
and space (including consequences and risks of slow and poor
recoveries) (Lewis, 1999;
Cutter et al., 2000; Turner et al., 2003; Adger, 2006).
However, the sustainability vulnerability framework does not
offer a forum for
analyzing how various social actors use scaled sociopolitical

processes and structures to
both facilitate and constrain access to capital, which in turn
influences an individual’s or
community’s vulnerability to external shocks. The geographical
concepts of relational
scale and place fulfil these analytical requirements.
The dynamics of relational scale
Stemming from geographical theory on spatial organization,
relational scale recognizes
scale as a fluid and dynamic sociopolitical construct that
reflects the subjectivity of
historical and contemporary power processes. Through the
deconstruction of ‘natural-
ized’ scales of social organization (such as national, regional,
local, and so on), relational
scale explores the way in which actors simultaneously use
multiple scaled social pro-
cesses and supporting structures to either reinforce the uneven
balance of power within
a given society or create new landscapes of power, recognition
and opportunity (Howitt,
1993; Ellem, 2002; Herod & Wright, 2002). The angle depends
on the politicized
agendas or positionality of the actors involved. Put simply,
knowing which political
buttons to press and at what scale is crucial in bringing about a
favourable outcome.
Recognizing scale as an expression of power and control over
capital, relational scale
adds depth and dynamism to Turner et al.’s (2003) vulnerability
framework by exposing
the underlying sociopolitical processes and corresponding
structures that perpetuate
social inequality, and the agendas that drive them. This creates

an invaluable medium
for analyzing the vulnerability of tourism communities in three
ways. First, its focus on
stakeholder dynamics requires the identification of the various
actors that influence
destination vulnerability. Second, it explores how these
stakeholders position them-
selves within the political arena to increase their access to
capital. Finally, the identifi-
cation of key stakeholders with vested interests in tourism
development and the
multiscaled structures they work through provide planners,
policy makers and commu-
nity members with a clear directive regarding the type of
resilience strategies required,
the target audience and the most appropriate scales for policy
intervention.
Place: a sociopolitically charged landscape
Place provides a theoretical lens through which to define Khao
Lak as the subject
of study and ‘situate’ it within the wider structures and
processes that influence
its vulnerability. The concept of place is more than a physical
location or politically
Vulnerability
Exposure Sensitivity Resilience
Adjustment and
adaptation/response

(e.g. newprogrammes, policy,
& autonomous options)
Impact/response
(e.g. loss of life,
economic production,
soil, ecosystem
service)
Coping/
response
(e.g. extant
programmes,
policy,
autonomous
options)
Human conditions
social/human capital & endowments
(e.g. population, entitlements,
institutions, economic structures)
Environmental conditions
natural capital/biophysical
endowments
(e.g. soil, water, climate,
minerals, ecosystemstructure
& function)
Components
(e.g. individuals,

households,
classes, firms,
states, flora/fauna,
ecosystems)
Characteristics
(e.g. frequency,
magnitude,
duration)
Figure 1. Interactive components of vulnerability within a given
place from Turner et al. (2003: 8077,
Figure 4). Inset figure at the top left refers to the full
vulnerability framework at Figure 2 below. (Copyright
(2003) National Academy of Sciences, USA; reproduced with
permission.)
Adjustment &
adaptation/
response
Coping/
response
Vulnerability
Characteristics
& components
of exposure
Human

conditions
Environmental
conditions
Impact/
response
Interactions of hazards
(perturbations, stresses,
stressors)
Variability & change
in human conditions
Variability & change
in environmental
conditions
Environmental influences outside the place
State of biosphere, state of nature,
global environmental changes
Impact/
responses
Adjustment &
adaptation/
response
Human influences outside the place
Macro political economy, institutions,

global trends and transitions
ConsequencesDrivers/causes
System operates at multiple
spatial, functional and
temporal scales
World
Region
Place
Dynamics
Cross-scale
In place
Beyond place
Figure 2. The sustainability vulnerability framework proposed
by Turner et al. (2003: 8076, Figure 3).
(Copyright (2003) National Academy of Sciences, USA;
reproduced with permission.)
demarcated space. Place embodies a sociopolitically charged
landscape infused with
multiple layers of meaning, collective identities, experiences
and understandings devel-
oped over time and space (Massey, 1993). Like vulnerability,
place is an ever evolving
multifaceted creation of social processes and human agency.
The uniqueness of place

derives from a distinct blend of localized and wider social
interactions operating outside
a given place and a historical layering of events particular to
that area (Massey, 1993).
However, underlying the subjective construction of place is the
power of definition
(Cresswell, 1999).
Place as a sociopolitical product of multiple images, identities
and interactions is
embodied in the systematic creation of the tourism product. The
product encapsulated
in the tourism destination is a blend of multilayered
imaginations constructed and
defined by tour operators and key destination stakeholders in
accordance with the
perceived expectations and desires of the travelling public
(Pritchard & Morgan, 2000;
Young, 1999). In this sense, places are reinterpreted,
reimagined, designed and mar-
keted (Knox & Marston, 2004) as manufactured and ‘placed’
images that are sold to
tourists (Nijman, 1999). The identification of who carries out
the reimaging and cultural
packaging and on what terms (Knox & Marston, 2004) are key
to understanding
important power dynamics that not only mould the tourism
product, but may also
influence the destination’s vulnerability.
Methodology
Considering the place-specific nature of vulnerability, case
study analysis has come to
dominate vulnerability assessment based on its capacity to
deconstruct complex and

place-based phenomena. Khao Lak was chosen as the case study
because it was the
worst affected tourism destination across Asia and Africa in
terms of lives lost and
property damage. Three qualitative methods were used to
identify the factors and
processes that contribute to Khao Lak’s vulnerability to shocks.
An exploratory litera-
ture review together with secondary document analysis (of
newspaper reports, NGO
recovery reports and various official and government
documents) identified preliminary
causal factors that heightened Khao Lak’s vulnerability to the
tsunami, which in turn,
shaped relevant questions for semistructured field interviews.
Twenty-four interviews
with tourism stakeholders (8 in Bangkok, 1 in Phuket and 15 in
Khao Lak) were
undertaken over a one-month period in mid-2005 to verify and
build upon the factors
identified from the secondary data, supplemented by ongoing
updates. Interview par-
ticipants included national, provincial, district and subdistrict
government representa-
tives, nongovernmental organization (NGO) representatives,
environmental action
group members, research institute and media representatives,
and tourism industry
representatives from small and medium enterprises (SMEs) in
Khao Lak. The Bangkok
and Phuket participants were selected for their knowledge of the
tourism industry and
Thai government structures, plus their involvement in the
recovery process. Khao Lak
participants were identified using snowballing techniques. As
many interviews were

conducted on condition of anonymity, the names of some
individuals quoted here are
withheld.
Khao Lak: beautiful and booming one day, gone the next
Khao Lak is a new coastal resort destination that had grown
from 100 rooms in 1996 to
5315 rooms by December 2004.1 Located on Thailand’s
southwest Andaman Coast, in
Takuapa District, Phang Nga Province, and bordered by Khao
Lak-Lamru National Park,
the heart of the destination extends from Khao Lak Beach
northwards to Laem
Pakarang (or Coral Cape) (Figure 3). Positioned within the
competitive Thai tourism
market as an alternative to its bustling neighbouring destination
of Phuket
(98 km to the south), Khao Lak is marketed as a peaceful haven
for nature lovers who
want to relax. Tourists attracted to Khao Lak are predominantly
German and Swedish
families and retirees escaping the European winter.
The service community that has grown with the destination
mainly comprises
locally owned SMEs including resorts, restaurants, souvenir
shops, tailoring and
health spa facilities, taxi and guide services, and scuba diving
companies. Khao Lak’s
4- and 5-star resort developments, owned by both local

investors and international
chains, only appeared after 2000 but their numbers have
increased since the tsunami,
whereas many smaller businesses have lacked the financial and
psychological strength
to rebuild. Strong tourist demand is generated through locally
run accommodation
websites, travel guidebooks and the promotions of European
tour operators including
TUI AG (Touristik Union International Aktiengesellschaft) and
Thomas Cook. Con-
0 10 20 30 40km
N
Phuket 98km
Krabi 171 km
Takuapa
30km
Bus
Station
Market
International
Tsunami
Museum
TonPling
Waterfall
Tap LamuPier

KHAO LAK
BEACH
NANG THONG
BEACH
BANG NIANG
BEACH
KHUK KHAK
BEACH
LAEM
PAKARANG
ANDAMAN
SEA
P
h
e
tk
a
s
e
m
N
a
tio
n
a
l

H
ig
h
w
a
y
N
o
.
4
KhaoLak-Lamru
National Park
Office
Khao
Lak-
Lamru
National
Park
Tsunami
Memorial
Penang
Banda Aceh
Sumatra
(INDONESIA)

BANGKOK
Phuket
THAILAND
GULF
OF THAILAND
ANDAMAN
SEA
MALAYSIA
MYANMAR
STRAIT
OF MALACCA
Earthquake
epicentre PUTRAJAYA
Krabi
N
Study area of
Khao Lak
0 200km
Figure 3. Location map of Khao Lak in Phang Nga Province,
southern Thailand; the dotted line approxi-

mates the tsunami-eroded beachfront.
stant demand fills the resorts to full capacity for six months
between October and
March, providing enough earnings to sustain the community
through the wet low
season (averaging 30 per cent capacity).
During the December 2004 tsunami, 10.6-m-high waves
penetrated up to 2 km
inland, destroying approximately 90 per cent of the hotel rooms
available in Khao Lak
(Bangkok Post, 2005). Seventy per cent of the 8212 deaths in
Thailand occurred in Phang
Nga Province (ADPC, 2006). Estimates suggest that 358 of
Khao Lak’s tourism employ-
ees lost their lives along with 2229 foreigners (ADPC, 2006;
director, Department of
Labour, Phang Nga Province, pers. comm., Phang Nga, 7
February 2007). Those workers
who survived were left with no jobs, no income and few
livelihood alternatives to
support a recovery.
Case study findings: the vulnerability of Khao Lak
deconstructed
Disasters such as the 2004 tsunami dramatically expose the
strengths and weaknesses of
the affected community’s socioenvironmental system and thus
its vulnerability to
shocks (Pelling, 2003; Wisner et al., 2004). But disasters can

also be catalysts for change
(Oliver-Smith, 1996; Lewis, 1999). Reflecting the complex
nature of vulnerability, the
presentation of the causal factors is neither simple nor linear;
the factors feed into and
off each other. Accordingly, we use a conceptual structure
based on Turner et al.’s (2003)
framework to explore the causal factors that have contributed
respectively to the
exposure, sensitivity and resilience of the Khao Lak community
to the tsunami. Woven
throughout the analysis are elucidations into how these factors
are socially constructed
and reinforced by economic development processes, uneven
access to resources, weak
governance and the competing agendas of key stakeholders. An
overview of the 13
three-dimensional factors that underlie Khao Lak’s vulnerability
and the scales at which
they are constructed is presented in Figure 4.
Exposure
An examination of Khao Lak’s natural and developmental
characteristics revealed two
interlinked factors that heightened the primarily coastal-based
community’s exposure to
the tsunami: flat coastal terrain lacking environmental defences
and inappropriate
coastal development.
Nature of the physical terrain. The nature of the coastal terrain
where much tourism
development is found (Murphy & Bayley, 1989) is a key
contributor to Khao Lak’s
exposure to coastal hazards (senior Thai researcher, Thailand
Institute of Scientific And

Technological Research, pers. comm., Bangkok, 29 June 2005).
Khao Lak’s tourism
facilities are concentrated along a strip of flat land that extends
2 km inland to the foot
of an escarpment. This, along with the clearing of the original
deep-rooted forest,
grasslands and rubber plantations, heightened the coastline’s
susceptibility to erosion
and left the built environment with no buffer against the force
of the waves (Thai
environmentalist, Toward Ecological Recovery and Regional
Alliance (TERRA), pers.
comm., Bangkok, 29 June 2005). Developments on higher
ground in the hills fronting
Khao Lak Beach sustained little damage.
Placement and type of development. Jeff McNeely, chief
scientist of the International
Union for Conservation of Nature (IUCN), attributed the
enormous loss of life from
the 2004 tsunami to the human intrusion on natural shorelines
typified by the
inappropriate developments that line the Indian Ocean coastal
rim (Bangkok Post, 2004).
In Khao Lak, the proximity of many resorts to the flat exposed
beach – sited to capitalize
on the foreshore terrain and beach views – coupled with the
types of structures built,
clearly heightened the physical exposure to coastal hazards.
Provincial building regulations stipulated a 30-m setback from

the natural vegeta-
tion line but did not include structural codes (government
officer, Khuk Khak Sub-
district, pers. comm., Khao Lak, 8 July 2005). Smaller
structures (mainly bungalow
clusters) were largely built out of wood while many larger
resorts were constructed from
concrete. The pattern of destruction caused by the tsunami
indicates the unsuitability of
the beach-facing developments in Khao Lak. Entering the
buildings through the large
sea-fronting windows, the tsunami waves demolished the
wooden structures and gutted
the concrete structures. Concrete buildings constructed
perpendicular to the shoreline,
however, remained structurally intact. Ensuring that safety
standards are not compro-
mised to fulfil tourist demands for water views is a continuing
challenge for Thai
tourism communities and planners.
Sensitivity
According to Adger (2003) and Hewitt (1997), a system’s
ability to absorb external
shocks and recover rests with the robustness and effectiveness
of preexisting governance
systems and social networks that control a community’s access
to resources. Findings
confirm that Khao Lak’s sensitivity was heightened by factors
relating to the local
private sector’s differential access to resources, the aptitude of
governance structures
and agendas of stakeholders who work through these structures,
as well as the desti-
nation’s dependency on highly seasonal tourism flows.

Key
International
National
Regional
Local
Human Conditions
Limited livelihood options
Access to economic capital
and insurance
Pre-existing weakness of
government structure and
processes
Unpreparedness for natural
hazards
Human conditions
Vulnerability of Khao Lak to the 2004 tsunami
Components
Natural terrain

Development
style
Adjustment and
adaptation/response
Early warning system
Post-tsunami tourism strategy
Natural resource management
Resilient market base
Robust marketing strategies
Impact/
response
Government-
led financial
assistance
Coping/
response
Strong local
representation
Figure 4. Scaled causal factors contributing to Khao Lak’s
vulnerability following Turner et al.’s (2003)
vulnerability framework.

Limited livelihood options and seasonality. Livelihood
diversification is a key strategy in
reducing vulnerability against multiple shocks (Moser et al.,
2001). Prior to the com-
mencement of tourism development in 1988, the greater Khao
Lak area was charac-
terized by sparsely populated villages that derived livelihoods
from rubber and fruit
plantations, and subsistence fishing. Tourism created new
opportunities for people to
start up businesses that provided hundreds of jobs …
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Portions © 2011 Saylor Publications, Inc.
ISBN 978-1-57218-305-6
Published November 2014 for the year 2015
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http://craftsman-book.com/
http://www.craftsmansitelicense.com
Contents of This Manual
3
Explanation of the Cost Tables ................................ 4
Area Modification Factors ........................................ 7
Construction Cost Index .......................................... 9
Residential Structures Section ...............................10
Single Family Residences .............................................. 10
Manufactured Housing................................................... 16
Multi-Family Residences ................................................ 19
Motels............................................................................. 23
Additional Costs for Residences.................................... 27
Multi-Family and Motel Garages .................................... 31
Cabins and Recreational Dwellings ............................... 32
Conventional Recreational Dwellings............................. 33
“A-Frame” Cabins .......................................................... 38
Additional Costs for Recreational Dwellings .................. 42
Life in Years and Depreciation for Residences .............. 43
Public Buildings Section .........................................44
Elementary Schools ....................................................... 44
Secondary Schools ........................................................ 53
Government Buildings.................................................... 56
Public Libraries............................................................... 62
Fire Stations ................................................................... 68

Commercial Structures Section ..............................74
Urban Stores, Masonry or Concrete .............................. 76
Urban Stores, Wood or Wood and Steel ....................... 82
Suburban Stores, Masonry or Concrete ........................ 89
Suburban Stores, Wood or Wood and Steel.................. 94
Supermarkets, Masonry or Concrete ........................... 103
Supermarkets, Wood or Wood and Steel .................... 105
Small Food Stores, Masonry or Concrete.................... 107
Small Food Stores, Wood Frame................................. 109
Discount Houses, Masonry or Concrete...................... 111
Discount Houses, Wood or Wood and Steel ............... 113
Banks and Savings Offices, Masonry or Concrete ...... 115
Banks and Savings Office, Wood Frame ..................... 120
Department Stores, Reinforced Concrete.................... 126
Department Stores, Masonry or Concrete ................... 129
Department Stores, Wood Frame ................................ 132
General Office Buildings, Masonry or Concrete .......... 135
General Office Buildings, Wood Frame ....................... 143
Medical-Dental Buildings, Masonry or Concrete ......... 151
Medical-Dental Buildings, Wood Frame ...................... 159
Convalescent Hospitals, Masonry or Concrete ........... 167
Convalescent Hospitals, Wood Frame ........................ 169
Funeral Homes............................................................. 171
Ecclesiastic Buildings .................................................. 173
Self Service Restaurants .............................................. 175
Coffee Shop Restaurants ............................................. 178
Conventional Restaurants ............................................ 181
“A-Frame” Restaurants ................................................ 183
Theaters, Masonry or Concrete.................................... 185
Mobile Home Parks...................................................... 192
Service Stations, Wood, Masonry or Steel ................... 198
Service Stations, Porcelain Finished Steel ................... 200
Service Stations, Ranch or Rustic ................................ 202
Additional Costs for Service Stations ........................... 204

Service Garages, Masonry or Concrete....................... 208
Service Garages, Wood Frame.................................... 213
Auto Service Centers, Masonry or Concrete................ 218
Industrial Structures Section................................ 222
Warehouses ................................................................. 224
Light Industrial Buildings .............................................. 225
Factory Buildings ......................................................... 226
Internal Offices ............................................................. 227
External Offices ............................................................ 227
Steel Buildings.............................................................. 228
Alternate Costs for Steel Buildings............................... 230
Commercial and Industrial Building Lives.................... 235
Additional Commercial and Industrial Costs................ 236
Material Handling System ............................................ 242
Display Fronts .............................................................. 243
Satellite Receiver Systems ........................................... 245
Signs ............................................................................ 246
Yard Improvements ...................................................... 247
Agricultural Structures Section ............................ 249
General Purpose Barns ................................................ 250
Hay Storage Barns ....................................................... 251
Feed Barns ................................................................... 252
Shop Buildings ............................................................. 253
Machinery and Equipment Sheds................................ 254
Small Sheds ................................................................. 255
Pole Barns .................................................................... 256
Low Cost Dairy Barns................................................... 257
Stanchion Dairy Barns.................................................. 258
Walk-Through Dairy Barns ........................................... 259
Modern Herringbone Barns ......................................... 260
Miscellaneous Dairy Costs........................................... 261
Poultry Houses, Conventional ...................................... 262
Poultry Houses, Modern Type...................................... 263
Poultry Houses, High Rise Type .................................. 264

Poultry Houses, Deep Pit Type .................................... 265
Poultry House Equipment ............................................ 266
Green Houses .............................................................. 267
Migrant Worker Housing .............................................. 268
Miscellaneous Agricultural Structures .......................... 269
Typical Lives for Agricultural Buildings......................... 269
Military Construction Section............................... 270
Facility Costs ........................................................ 271
Index ...................................................................... 273
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Explanation of the Cost Tables
4
This manual shows construction or replacement
costs for a wide variety of residential, commercial,
industrial, public, agricultural and military buildings.
For your convenience and to minimize the chance
of an error, all the cost and reference information

you need for each building type is brought together
on two or three pages. After reading pages 4 to 6,
you should be able to turn directly to any building
type and create an error-free estimate or appraisal
of the construction or replacement cost.
The costs are per square foot of floor area for
the basic building and additional costs for optional
or extra components that differ from building to
building. Building shape, floor area, design
elements, materials used, and overall quality
influence the basic structure cost. These and other
cost variables are isolated for the building types.
Components included in the basic square foot cost
are listed with each building type. Instructions for
using the basic building costs are included above
the cost tables. These instructions include a list of
components that may have to be added to the
basic cost to find the total cost for your structure.
The figures in this manual are intended to reflect
the amount that would be paid by the first user of a
building completed in mid 2015.
Costs in the tables include all construction costs:
labor, material, equipment, plans, building permit,
supervision, overhead and profit. Cost tables do
not include land value, site development costs,
government mandated fees (other than the building
permit) or the cost of modifying unusual soil
conditions or grades. Construction expense may
represent as much as 60% or as little as 40% of the
cost to the first building owner. Site preparation,
utility lines, government fees and mandates,
finance cost and marketing are not part of the
construction cost and may be as much as 20% of

the cost to the first building owner.
Building Quality
Structures vary widely in quality and the quality
of construction is the most significant variable in the
finished cost. For estimating purposes the structure
should be placed in one or more quality classes.
These classes are numbered from 1 which is the
highest quality generally encountered. Each section
of this manual has a page describing typical
specifications which define the quality class.
Each number class has been assigned a word
description (such as best, good, average or low)
for convenience and to help avoid possible errors.
The quality specifications do not reflect some
design features and construction details that can
make a building both more desirable and more
costly. When substantially more than basic design
elements are present, and when these elements
add significantly to the cost, it is appropriate to
classify the quality of the building as higher than
would be warranted by the materials used in
construction.
Many structures do not fall into a single class
and have features of two quality classes. The tables
have “half classes” which apply to structures which
have some features of one class and some
features of a higher or lower class. Classify a
building into a “half class” when the quality
elements are fairly evenly divided between two
classes. Generally, quality elements do not vary
widely in a single building. For example, it would be

unusual to find a top quality single family residence
with minimum quality roof cover. The most weight
should be given to quality elements that have the
greatest cost. For example, the type of wall and
roof framing or the quality of interior finish are more
significant than the roof cover or bathroom wall
finish. Careful evaluation may determine that
certain structures fall into two distinct classes. In
this case, the cost of each part of the building
should be evaluated separately.
Building Shapes
Shape classification considers any cost
differences that arise from variations in building
outline. Shape classification considerations vary
somewhat with different building types. Where the
building shape often varies widely between
buildings and shape has a significant effect on the
building cost, basic building costs are given for
several shapes. Use the table that most closely
matches the shape of the building you are
evaluating. If the shape falls near the division
between two basic building cost tables, it is
appropriate to average the square foot cost from
those two tables.
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5
Area of Buildings
The basic building cost tables reflect the fact
that larger buildings generally cost less per square
foot than smaller buildings. The cost tables are
based on square foot areas which include the
following:
1. All floor area within and including the exterior
walls of the main building.
2. Inset areas such as vestibules, entrances or
porches outside of the exterior wall but under the
main roof.
3. Any enclosed additions, annexes or lean-tos with
a square foot cost greater than three-fourths of
the square foot cost of the main building.
Select the basic building cost listed below the
area which falls closest to the actual area of your
building. If the area of your building falls nearly mid-
way between two listed building areas, it is
appropriate to average the square foot costs for the
listed areas.

Wall Heights
Building costs are based on the wall heights
given in the instructions for each building cost
table. Wall height for the various floors of a building
are computed as follows: The basement is
measured from the bottom of floor slab to the
bottom of the first floor slab or joist. The main or
first floor extends from the bottom of the first floor
slab or joist to the top of the roof slab or ceiling
joist. Upper floors are measured from the top of the
floor slab or floor joist to the top of the roof slab or
ceiling joist. These measurements may be
illustrated as follows:
Square foot costs of most building design types
must be adjusted if the actual wall height differs
from the listed wall height. Wall height adjustment
tables are included for buildings requiring this
adjustment. Wall height adjustment tables list
square foot costs for a foot of difference in
perimeter wall height of buildings of various areas.
The amount applicable to the actual building area
is added or deducted for each foot of difference
from the basic wall height.
Buildings such as residences, medical-dental
buildings, funeral homes and convalescent

hospitals usually have a standard 8-foot ceiling
height except in chapels or day room areas. If a
significant cost difference exists due to a wall
height variation, this factor should be considered in
establishing the quality class.
Other Adjustments
A common wall exists when two buildings share
one wall. Common wall adjustments are made by
deducting the in-place cost of the exterior wall
finish plus one-half of the in-place cost of the
structural portion of the common wall area.
If an owner has no ownership in a wall, the in-
place cost of the exterior wall finish plus the in-
place cost of the structural portion of the wall
should be deducted from the total building costs.
Suggested common wall and no wall ownership
costs are included for many of the building types.
Some square foot costs include the cost of
expensive veneer finishes on the entire perimeter
wall. When these buildings butt against other
buildings, adjustments should be made for the lack
of this finish. Where applicable, linear foot cost
deductions are provided.
The square foot costs in this manual are based
on composite costs of total buildings including
usual work room or storage areas. They are
intended to be applied on a 100% basis to the total
building area even though certain areas may or
may not have interior finish. Only in rare instances
will it be necessary to modify the square foot cost
of a portion of a building.

Multiple story buildings usually share a common
roof structure and cover, a common foundation
and common floor or ceiling structures. The costs
of these components are included in the various
floor levels as follows:
Basement
1s t story
Upper stories
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6
The first or main floor includes the cost of a floor
structure built at ground level, foundation costs for
a one-story building, a complete ceiling and roof

structure, and a roof cover. The basement includes
the basement floor structure and the difference
between the cost of the first floor structure built at
ground level and its cost built over a basement.
The second floor includes the difference between
the cost of a foundation for a one-story building
and the cost of a foundation for a two-story building
and the cost of the second story floor structure.
Location Adjustments
The figures in this manual are intended as
national averages for metropolitan areas of the
United States. Use the information on page 7 to
adapt the basic building costs to any area listed.
Frequently building costs outside metropolitan
areas are 2% to 6% lower if skilled, productive,
lower cost labor is available in the area. The factors
on page 7 can be applied to nearly all the square
foot costs and some of the “additional” costs in this
book.
Temporary working conditions in any community
can affect construction and replacement costs.
Construction which must be done under deadline
pressure or in adverse weather conditions or after a
major fire, flood, or hurricane or in a thin labor
market can temporarily inflate costs 25% to 50%.
Conditions such as these are usually temporary
and affect only a limited area. But the higher costs
are real and must be considered, no matter how
limited the area and how transient the condition.
Depreciation
Depreciation is the loss in value of a structure

from all causes and is caused primarily by three
forms of obsolescence: (1) physical (2) functional,
and (3) economic.
Physical obsolescence is the deterioration of
building components such as paint, carpets or
roofing. Much of this deterioration is totally curable.
The physical life tables on pages 43, 235 and 269
assume normal physical obsolescence. Good
judgment is required to evaluate how deferred
maintenance or rehabilitation will reduce or extend the
anticipated physical life of a building.
Functional obsolescence is due to some
deficiency or flaw in the building. For example, too
few bathrooms for the number of bedrooms or an
exceptionally high ceiling can reduce the life
expectancy of a residence. Some functional
obsolescence can be cured. The physical life
tables do not consider functional obsolescence.
Economic obsolescence is caused by
conditions that occur off site and are beyond
control of the owner. Examples of economic
obsolescence include a store in an area of
declining economic activity or obsolescence
caused by governmental regulation (such as a
change in zoning). Because this kind of
obsolescence is particularly difficult to measure, it
is not considered in the physical life tables.
“Effective age” considers all forms of
depreciation. It may be less than chronological
age, if recently remodeled or improved, or more
than the actual age, if deterioration is particularly

bad. Though effective age is not considered in the
physical life tables, it may yield a better picture of a
structure's life than the actual physical age. Once
the effective age is determined, considering
physical, functional and economic deterioration,
use the percent good tables on pages 43, 235 or
269 to determine the present value of a
depreciated building. Present value is the result of
multiplying the replacement cost (found by using
the cost tables) by the appropriate percent good.
Limitations
This manual will be a useful reference for anyone
who has to develop budget estimates or
replacement costs for buildings. Anyone familiar
with construction estimating understands that even
very competent estimators with complete working
drawings, full specifications and precise labor and
material costs can disagree on the cost of a
building. Frequently exhaustive estimates for even
relatively simple structures can vary 10% or more.
The range of competitive bids on some building
projects is as much as 20%. Estimating costs is not
an exact science and there’s room for legitimate
disagreement on what the “right” cost is. This
manual can not help you do in a few minutes what
skilled estimators may not be able to do in many
hours. This manual will help you determine a
reasonable replacement or construction cost for
most buildings. It is not intended as a substitute for
judgment or as a replacement for sound
professional practice, but should prove a valuable
aid to developing an informed opinion of value.
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Area Modification Factors
Construction costs are higher in some cities than in
other cities. Add or deduct the percentage shown on this
page or page 8 to adapt the costs in this book to your job
site. Adjust your estimated total project cost by the per-
centage shown for the appropriate city in this table to find
your total estimated cost. Where 0% is shown it means no
modification is required. Factors for Canada adjust to
Canadian dollars.
These percentages were compiled by comparing the
construction cost of buildings in nearly 600 communities
throughout North America. Because these percentages
are based on completed projects, they consider all con-
struction cost variables, including labor, equipment and
material cost, labor productivity, climate, job conditions
and markup.
Modification factors are listed alphabetically by state
and city, followed by the first three digits of the postal zip

code.
These percentages are composites of many costs and
will not necessarily be accurate when estimating the cost
of any particular part of a building. But when used to
modify costs for an entire structure, they should improve
the accuracy of your estimates.
7
Alabama Average -6%
Anniston 362 -9%
Auburn 368 -6%
Bellamy 369 -3%
Birmingham 350-352 3%
Dothan 363 -6%
Evergreen 364 -12%
Gadsden 359 -13%
Huntsville 358 -3%
Jasper 355 -11%
Mobile 365-366 -3%
Montgomery 360-361 -2%
Scottsboro 357 -6%
Selma 367 -6%
Sheffield 356 -1%
Tuscaloosa 354 -5%
Alaska Average 21%
Anchorage 995 27%
Fairbanks 997 24%
Juneau 998 22%
Ketchikan 999 11%
King Salmon 996 24%
Arizona Average -4%
Chambers 865 -4%

Douglas 855 -3%
Flagstaff 860 -9%
Kingman 864 -5%
Mesa 852 1%
Phoenix 850 1%
Prescott 863 -7%
Show Low 859 -9%
Tucson 856-857 -6%
Yuma 853 0%
Arkansas Average -7%
Batesville 725 -10%
Camden 717 -5%
Fayetteville 727 -5%
Fort Smith 729 -7%
Harrison 726 -14%
Hope 718 -1%
Hot Springs 719 -13%
Jonesboro 724 -8%
Little Rock 720-722 -3%
Pine Bluff 716 -2%
Russellville 728 -6%
West Memphis 723 -6%
California Average 8%
Alhambra 917-918 9%
Bakersfield 932-933 3%
El Centro 922 -1%
Eureka 955 -4%
Fresno 936-938 -1%
Herlong 961 -1%
Inglewood 902-905 9%
Irvine 926-927 13%
Lompoc 934 6%
Long Beach 907-908 10%
Los Angeles 900-901 8%

Marysville 959 -1%
Modesto 953 -1%
Mojave 935 6%
Novato 949 13%
Oakland 945-947 19%
Orange 928 12%
Oxnard 930 4%
Pasadena 910-912 9%
Rancho Cordova 956-957 6%
Redding 960 -3%
Richmond 948 19%
Riverside 925 3%
Sacramento 958 6%
Salinas 939 3%
San Bernardino 923-924 4%
San Diego 919-921 7%
San Francisco 941 28%
San Jose 950-951 18%
San Mateo 943-944 20%
Santa Barbara 931 6%
Santa Rosa 954 6%
Stockton 952 1%
Sunnyvale 940 20%
Van Nuys 913-916 8%
Whittier 906 8%
Colorado Average 1%
Aurora 800-801 6%
Boulder 803-804 3%
Colorado Springs 808-809 -1%
Denver 802 6%
Durango 813 0%
Fort Morgan 807 -3%
Glenwood Springs 816 4%
Grand Junction 814-815 -1%

Greeley 806 4%
Longmont 805 2%
Pagosa Springs 811 -6%
Pueblo 810 2%
Salida 812 -5%
Connecticuit Average 12%
Bridgeport 066 12%
Bristol 060 12%
Fairfield 064 14%
Hartford 061 14%
New Haven 065 12%
Norwich 063 8%
Stamford 068-069 16%
Waterbury 067 12%
West Hartford 062 9%
Delaware Average 2%
Dover 199 -5%
Newark 197 7%
Wilmington 198 5%
District of Columbia
Average 12%
Washington 200-205 12%
Florida Average -7%
Altamonte Springs 327 -6%
Bradenton 342 -8%
Brooksville 346 -9%
Daytona Beach 321 -12%
Fort Lauderdale 333 -1%
Fort Myers 339 -9%
Fort Pierce 349 -13%
Gainesville 326 -9%

Jacksonville 322 -4%
Lakeland 338 -8%
Melbourne 329 -10%
Miami 330-332 -2%
Naples 341 -5%
Ocala 344 -13%
Orlando 328 -2%
Panama City 324 -12%
Pensacola 325 -9%
Saint Augustine 320 -7%
Saint Cloud 347 -5%
St Petersburg 337 -7%
Tallahassee 323 -9%
Tampa 335-336 -3%
West Palm Beach 334 -3%
Georgia Average -4%
Albany 317 -9%
Athens 306 -6%
Atlanta 303 13%
Augusta 308-309 -4%
Buford 305 -4%
Calhoun 307 -11%
Columbus 318-319 -6%
Dublin/Fort Valley 310 -9%
Hinesville 313 -6%
Kings Bay 315 -4%
Macon 312 -3%
Marietta 300-302 4%
Savannah 314 -5%
Statesboro 304 -11%
Valdosta 316 -3%
Hawaii Average 24%
Aliamanu 968 25%

Ewa 967 23%
Halawa Heights 967 23%
Hilo 967 23%
Honolulu 968 25%
Kailua 968 25%
Lualualei 967 23%
Mililani Town 967 23%
Pearl City 967 23%
Wahiawa 967 23%
Waianae 967 23%
Wailuku (Maui) 967 23%
Idaho Average -9%
Boise 837 -2%
Coeur d’Alene 838 -11%
Idaho Falls 834 -8%
Lewiston 835 -12%
Meridian 836 -9%
Pocatello 832 -10%
Sun Valley 833 -10%
Illinois Average 5%
Arlington Heights 600 16%
Aurora 605 15%
Belleville 622 0%
Bloomington 617 1%
Carbondale 629 -5%
Carol Stream 601 15%
Centralia 628 -3%
Champaign 618 0%
Chicago 606-608 17%
Decatur 623 -8%
Galesburg 614 -6%
Granite City 620 3%
Green River 612 4%
Joliet 604 16%

Kankakee 609 1%
Lawrenceville 624 -6%
Oak Park 603 19%
Peoria 615-606 7%
Peru 613 3%
Quincy 602 17%
Rockford 610-611 4%
Springfield 625-527 0%
Urbana 619 -3%
Indiana Average -2%
Aurora 470 -4%
Bloomington 474 -1%
Columbus 472 -4%
Elkhart 465 -4%
Evansville 476-477 4%
Fort Wayne 467-468 -3%
Gary 463-464 20%
Indianapolis 460-462 7%
Jasper 475 -8%
Jeffersonville 471 -4%
Kokomo 469 -8%
Lafayette 479 -6%
Muncie 473 -9%
South Bend 466 -3%
Terre Haute 478 -3%
Iowa Average -4%
Burlington 526 -3%
Carroll 514 -11%
Cedar Falls 506 -4%
Cedar Rapids 522-524 3%
Cherokee 510 -1%
Council Bluffs 515 -1%
Creston 508 -8%

Davenport 527-528 3%
Decorah 521 -7%
Des Moines 500-503 4%
Dubuque 520 -3%
Fort Dodge 505 -3%
Mason City 504 -3%
Ottumwa 525 -6%
Sheldon 512 -8%
Shenandoah 516 -13%
Sioux City 511 3%
Spencer 513 -8%
Waterloo 507 -5%
Kansas Average -7%
Colby 677 -7%
Concordia 669 -13%
Dodge City 678 -6%
Emporia 668 -5%
Fort Scott 667 -8%
Hays 676 -13%
Hutchinson 675 -7%
Independence 673 0%
Liberal 679 -7%
Salina 674 -8%
Wichita 670 -5%
Kentucky Average -4%
Ashland 411-412 -6%
Bowling Green 421 -5%
Campton 413-414 -10%
Covington 410 1%
Elizabethtown 427 -9%
Frankfort 406 -1%
Hazard 417-418 -6%
Hopkinsville 422 -7%
Lexington 403-405 2%

London 407-409 -7%
Louisville 400-402 1%
Owensboro 423 -3%
Paducah 420 -2%
Pikeville 415-416 -4%
Somerset 425-426 -10%
White Plains 424 -5%
Louisiana Average 0%
Alexandria 713-714 -4%
Baton Rouge 707-708 10%
Houma 703 6%
Lafayette 705 2%
Lake Charles 706 0%
Mandeville 704 -1%
Minden 710 -6%
Monroe 712 -9%
New Orleans 700-701 2%
Shreveport 711 -4%
Maine Average -7%
Auburn 042 -5%
Augusta 043 -8%
Bangor 044 -8%
Bath 045 -7%
Brunswick 046 -2%
Camden 047 -11%
Cutler 048 -10%
Dexter 049 -8%
Northern Area 050 -10%
Portland 051 0%
Maryland Average 2%
Annapolis 214 8%
Baltimore 210-212 8%

Bethesda 208-209 13%
Church Hill 216 -4%
Cumberland 215 -10%
Elkton 219 -2%
Frederick 217 5%
Laurel 206-207 9%
Salisbury 218 -6%
Massachusetts
Average 13%
Ayer 015-016 8%
Bedford 017 18%
Boston 021-022 34%
Brockton 023-024 21%
Cape Cod 026 4%
Chicopee 010 8%
Dedham 019 17%
Fitchburg 014 13%
Hingham 020 20%
Lawrence 018 16%
Nantucket 025 …
COURSE: CONSTRUCTION COST ANALYSIS AND
BIDDING
LEVEL: GRADUATE
ASSIGNMENT # 1
TOTAL POINTS: 100
LEARNING OBJECTIVES:

After successfully completing this assignment, students will be
able to:
• Differentiate between various construction processes
• Differentiate between various methods for cost estimation
Q1. Estimate the preliminary cost of constructing a single
family one-story, 2,000-ft2 average-
quality home (you can choose any location). The home is
constructed with wood siding on a
wood frame and includes a two-car detached garage, 300-ft2
porch, two and one-half baths, one
fireplace (internal chimney with two flues), cedar shakes, air-
conditioning utilizing the heating
ductwork, and a full, unfinished basement. You can use Means
Cost Data online, library copy or
the cost data sheet attached. Please refer all the cost resources
you have used for your work
(Include a list of assumptions (if any) you have made to
calculate the cost).
40 points
Cost Data Source
Attached cost data sheet will be sufficient for this assignment.

You can make any
assumptions as needed and provide the list of those assumption
in the beginning of the
assignment.
Q2. Search online for a copy of sample contract agreement
document and answer the
following questions (you have to attach the copy of sample
contract with your work):
a. What type of agreement (lump-sum, unit-price, or cost plus-
fee) is used for the project? If
it is a cost- plus-fee agreement, how is the fee determined, and
is there a guaranteed
maximum price?
b. What provisions are included in the contract documents
regarding the time of
completion? What penalties are there for failing to meet the
completion date? Is there a
bonus for completing the project ahead of schedule?
c. How are progress payments handled? When are they due?
How quickly will they be
paid?
d. Will retention be withheld? What are the requirements for the

release of retention?
e. How is final acceptance handled? What inspections are
required? What forms,
documents, maintenance and operation manuals, certifications,
red-line drawings, and so
on need to be submitted before final acceptance?
f. What bonds and insurances are needed for the job? 60 points
Data Sources
Some of the sample contract documents can be downloaded by
clicking the following links:
https://www.montrosecounty.net/DocumentCenter/View/823/Sa
mple-Construction-Contract
https://www.smgov.net/uploadedFiles/Departments/Public_Wor
ks/AdminSvcs_-
_Architecure/SAMPLE%20CONSTRUCTION%20CONTRACT
%20(4-16).pdf
https://uh.edu/legal-affairs/cmar_ogc-s-2013-01_revised-
05.01.2019.pdf
https://www.inf.gov.nt.ca/sites/inf/files/resources/construction_
contract_0.pdf
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Ethnicity, politics and inequality: post-
tsunami humanitarian aid delivery in
Ampara District, Sri Lanka
M.W. Amarasiri de Silva Professor, Department of Sociology,
Faculty of Arts,
University of Peradeniya, Sri Lanka
The provision of humanitarian aid at times of disaster in multi-
ethnic community settings may
lead to conflict, tension and even the widening of the distance
between various ethnic groups. That
aid agencies distribute humanitarian aid directly to affected
communities, to speed up recovery,
may often lead to chaos and the intensification of ethnic
sentiments. The new distribution mech-
anisms introduced for the delivery of tsunami aid in Ampara
District, Sri Lanka, did not recognise
local networks and the culture of the ethnically mixed
community setting. This paper analyses
post-tsunami aid distribution in Ampara and shows how such an
extemporised effort in an
ethnically cognisant context increased ethnic division,
inequality and disorder, while marginalis-
ing the poor segments of the affected population. It recommends
the inclusion of local networks in
aid dissemination as a measure for improving ethnic neutrality
and social harmony in disaster-hit
multi-ethnic communities.
Keywords: Ampara District, Asian tsunami, ethnicity,
humanitarian aid, Sri Lanka
Introduction
The Indian Ocean tsunami of 26 December 2004 is viewed

overall as a tragedy that
did not recognise ‘culturally derived discriminations and social
distinctions’ (Fritz,
1961, p. 685). Due to the enormity of the catastrophe, various
groups—rich and poor,
Sinhalese, Tamils and Muslims, and the Liberation Tigers of
Tamil Eelam (LTTE) and
the forces of the Government of Sri Lanka (GoSL)—were
suffering the ramifications
in the immediate aftermath.
In Ampara District on the east coast of Sri Lanka, however, the
picture is somewhat
different. The theory that the effects of disasters are
indiscriminate proved misplaced
here, since the people most affected largely comprised those on
the lower rungs of the
social ladder and in certain ethnically identifiable communities.
Disasters are seen
as ‘products’ of the economic, political and social environment
and of the natural
events that cause them. Poor people are most likely to be the
victims of disasters in
developing countries in particular (Blaikie et al., 1994; Peacock
and Girard, 1997).
Such social groups often consist of ethnic minorities and
excluded communities.
Ethnicity is thus an important index of increased vulnerability
to disasters in devel-
oping countries (Aptekar and Boore, 1990; Enarson, 1998;
Peacock and Girard, 1997;
Bates and Peacock, 1993; Peacock and Ragsdale, 1997).
doi:10.1111/j.0361-3666.2008.01073.x
Disasters, 2009, 33(2): 253−273. © 2009 The Author(s). Journal
compilation © Overseas Development Institute, 2009.

Published by Blackwell Publishing, 9600 Garsington Road,
Oxford, OX4 2DQ, UK and 350 Main Street, Malden, MA
02148, USA
M.W. Amarasiri de Silva254
In ethnically mixed communities, the distribution of economic
and political power
has implications for coping with disaster-based vulnerabilities
(Fothergill, Maestas
and Darlington, 1999). Disaster vulnerability among racial and
ethnic minority com-
munities has reportedly increased in the recent past (Anderson,
1996; Peacock and
Girard, 1997). Significant differences in risk perception among
different ethnic groups
vis-à-vis disaster events have been reported (Ives and Furseth,
1983); and different
consequences of hazards for ethnic minorities have been
highlighted (Hutton, 1976;
Bates et al., 1963).
In terms of fatalities and other effects of the tsunami, the poor
Muslim commu-
nities in the coastal areas of Ampara suffered particularly badly.
Rates of mortality,
morbidity and damage to property were extremely high among
the politically less
powerful Muslims in the coastal areas of Ampara compared to
those of the Sinhalese
and the Tamils. Locations most seriously affected on the east
coast were those inhabited
by the Muslims. Lower middle-class families in the affected
ethnic minority commu-
nities were less likely to attract subsidies and assistance, a fact

observed elsewhere as
well (Aptekar and Boore, 1990).
The unequal impact of the tsunami may have been precipitated
by the fact that
the Muslims lived along the coast, and the majority of them
were involved in the
fishing industry. The congested housing settlements of the
Muslims may have been
a factor in the higher levels of mortality and morbidity, as well
as physical damage.
That ethnic minorities on the east coast live in segregation, in
ribbon-like discrete
communities, and that, for historical reasons, Muslims in
particular reside in less
prestigious, low-lying places, hemmed in between the lagoon
and the sea, might have
heightened their vulnerability to the 2004 tsunami.
In the process of recovery, cultural boundaries have been
reinvented and culture-
based discrimination has resumed. During this process, some
people and community
groups sought advantages while others were deprived of
benefits and opportunities
for recovery. Despite the indiscriminate effects of disasters, it
is generally recognised
that disaster risk and vulnerability are not equally distributed,
particularly in the
recovery stage. Thus, the recovery process is seen as sensitive
to ethnicity and social
stratifications, especially those that emerge post disaster (Couch
and Kroll-Smith,
1985; Fordham, 1999; Morrow, 1997).
This paper argues that ethnicity has become the organising
principle in the post-
tsunami humanitarian aid distribution process in Ampara.
Ethno-political relation-

ships that existed in the pre-tsunami era in the District,
particularly between Muslims
and Tamils, were further ethnicised and intensified in the
process. The disadvan-
taged and vulnerable communities affected by the tsunami along
the coast of Ampara,
largely comprising poor Muslim fisher folk, were deprived of
the benefits of humani-
tarian aid. Creating highly centralised, elite-run mechanisms for
the distribution of
humanitarian aid in such multi-ethnic settings led to a widening
of the ethnic divide,
increasing inequalities and chaos, and thereby making the poor
and the marginal-
ised communities even poorer and more marginalised. As a
prelude to the analysis, the
paper first contextualises tsunami-affected areas in their
socio-economic setting in
Ampara District.
Ethnicity, politics and inequality 255
Ampara District in the Eastern Province
Ampara District in the Eastern Province of Sri Lanka, where the
research was con-
ducted between March and June 2006, covers an area of 4,431
square kilometres and
has a population of 635,332. Muslims (41.59 per cent),
Sinhalese (39.33 per cent) and
Tamils (18.76 per cent) constitute the major communities in the
District. Of the 20
District Secretariat (DS) divisions in Ampara, the tsunami
affected 10 along the
coastal belt. Muslims predominantly inhabit most of these. The

main livelihood in
these divisions is fisheries, while paddy production is the main
activity of the District
as a whole.
Muslims and Tamils live in juxtaposed, but discrete
communities, spread along
the coastal belt from south to north. Although the two
communities maintain eco-
nomic exchange and trade links, mutual trust between Muslims
and Tamils has been
eroded since the 1980s due to a heightening of political
activities. As in Muslim
villages in Trincomalee (Korf, 2004), the Muslim fisher folk
here are caught up in
the power struggle between the GoSL forces and the LTTE,
which has diminished
their ability to fish in the deep seas. Despite cultural and lingual
similarities, includ-
ing matrilocality and practising of the kudi system of
inheritance and naming (Yalman,
1967; McGilvray, 1982), the Muslims and Tamils of Ampara
view themselves as
separate ethnic groups, different from one another. Cultic
worship of Kannaki and
Mari Amman makes the Eastern Tamils unique. They also view
themselves as distinct
from the Tamils and Muslims living in the rest of Sri Lanka.
The March 2004 break-
away of Colonel Karuna or Karuna Amman, the leader of the
eastern faction of the
LTTE, further reflects the ethnic distinctiveness and identity of
the Eastern Tamils.
In the past, the Eastern Province was regarded as under the
control of the Jaffna
Tamils, who often held important positions in administration
and local govern-

ment. Over the past two decades, Muslim political leaders in
particular have pushed
for a stronger Muslim identity and have been instrumental in
setting up ethnically
segregated governance and welfare structures in Ampara. A
situation has gradually
evolved in which both Tamils and Muslims in the Eastern
Districts are seeking
greater political and administrative independence.
The Sinhalese communities, located in the interior and in the
southern tip of the
District, are not in direct confrontation with any of the other
ethnic groups in the
tsunami-affected areas of Ampara District. GoSL forces and the
LTTE operate
within their own territories, which were demarcated more or
less in the years after
the ceasefire agreement of 2002, with minimal trespass on
either side at the time of
the author’s fieldwork (March–June 2006).1
Ongoing power politics in the country influence the political
set-up of the District.
The pre-tsunami situation was that the Tamils (predominantly
the LTTE) and the
Muslims had political problems associated with land-related
matters. Both Muslim
and Tamil traders were subject to harassment and taxation by
militant groups, includ-
ing the LTTE. Riots involving Muslims and Tamils have
occurred since the 1990s
(Goodhand and Lewer, 1999). Muslim villagers in the Northern
Districts were
expelled by the LTTE at the beginning of its struggle for a
Tamil homeland or Eelam

Map 1 Grama Niladhari (GN) Divisions in Ampara District
affected by the 2004 tsunami
Source: Department of Census and Statistics, Sri Lanka.
(in the 1990s), and this affected mutual trust and relations
between these two ethnic
communities in the Eastern Province. Competition for political
power and economic
resources, including land, between Tamils and Muslims in
Ampara shows the deep
mistrust between them, although they were neighbours who
lived in adjacent com-
munities and engaged in trade and economic activities at the
time of the tsunami. It
is into this ethnically sensitive context that the tsunami entered
on 26 December 2004.
Tsunami recovery politics and actors
The territorial demarcations and political barriers that existed
before the tsunami
between the GoSL forces and the LTTE, and between the Tamils
and the Muslims,
were relaxed in the immediate wake of the tsunami, when both
the GoSL forces
and the LTTE commenced relief and welfare work for the
people. In this environ-
ment, civil society organisations were at ease in providing for

tsunami recovery
through existing local networks (Frerks and Klem, 2005). The
new development in
the Eastern Districts, particularly in Ampara, was seen as a
precursor to a renewed
peace process. These local non-governmental organisation
(NGO) and civil society
initiatives (Rodriguez et al., 2006) were viewed as a sign of
good things to come after
the tsunami.
It was in this context that the GoSL introduced an institutional
arrangement for
tsunami recovery and the reconstruction of the affected
communities: the Post-
Tsunami Operational Management Structure (P-TOMS).
P-TOMS was the regula-
tory outcome of the Joint Mechanism on Tsunami Aid
Distribution, signed between
the GoSL and high-level LTTE politicians on 24 June 2005.
P-TOMS, as proposed,
was to operate within a limited area of two kilometres from the
coastline, in the six
Districts of Ampara, Batticaloa, Jaffna, Kilinochchi, Mullaitivu
and Trincomalee
(Asian Tribune, 2005). Under this structure, there was no place
for the civil society
organisations that had played a key role in the early tsunami
recovery process (von
Braunmühl et al., 2006).
Following the signing of the agreement, there were major
demonstrations organ-
ised by predominantly Sinhala political parties—the Janatha
Vimukthi Peramuna
(JVP) and Jathika Hela Urumaya (JHU)—and by the Muslim
political parties (Pirani
and Kadirgamar, 2006). The protest leaders questioned the

legitimacy of P-TOMS
and its control over resources. The JVP left the GoSL coalition
as a result. The massive
opposition culminated in a hunger strike or fast-unto-death by
Dr Omalpe Sobhita,
a prominent member of the Buddhist clergy and a member of the
JHU, which was
called off only after then President Chandrika Bandaranaike
Kumaratunga pledged
to discuss the agreement with Buddhist prelates before it was
put into effect. The
four Maha Nayaka Theros2 of the Amarapura, Asgiriya,
Malwatte and Ramanya chap-
ters gathered to issue a Sangha Agna (command) and to summon
a mass gathering
to object to the signing of the Joint Mechanism between the
GoSL and the LTTE
(Lankanewspapers.com, 2005).
The Supreme Court of Sri Lanka ruled out certain clauses of
the accord, and this
proved to be the final nail in the coffin of P-TOMS. The LTTE
later reneged on
the P-TOMS agreement, saying that it would ‘refuse to work
under any authority
under the Sri Lankan government . . .’ (Asian Tribune, 2005).
The LTTE’s rejection
of a coordinated approach to tsunami recovery may have been
induced by the notion
that economic prosperity in the region would hamper its
struggle for Eelam.
The impact of the failed P-TOMS agreement reverberates to the
present day in
tsunami-affected Ampara District. The political manoeuvring
surrounding this accord
reinforced the importance of ethno-geopolitical identities and
the internationalisation

of the tsunami recovery process (Pirani and Kadirgamar, 2006;
Goodhand and Klem,
2005). The new aid delivery process created afterwards
involved various GoSL depart-
ments, the Government Agent of the District, the GoSL forces,
especially the Special
Task Force (STF), and the LTTE, including the Tamil
Rehabilitation Organisation
(TRO). The various civil society organisations that were
engaged in the recovery pro-
cess at the beginning were not included as key agents in the aid
delivery process. It is
unfortunate that the macro players, who took part in P-TOMS
and later in tsunami
aid delivery, did not pay attention to those civil society actors
and did nothing to utilise
participatory experience of recovery and reconstruction efforts
in Ampara District.
The attempt by the GoSL to establish P-TOMS is viewed here
as the product of
a misreading of the emerging cooperation among divergent civil
society groups and
local political organisations following the materialisation of a
burgeoning partner-
ship between the GoSL and the LTTE. Not only did the direct
intervention of the
GoSL, international NGOs and macro political parties impede
the opportunity to
create local participatory methodologies for post-tsunami
reconstruction, but also
the efforts that developed at the community level were nipped

in the bud by the fail-
ure to support them.
Sixty-four international NGOs in Ampara that were distributing
tsunami aid
formed the Ampara District Livelihood Coordination Committee
(or the Consortium
for Livelihood Coordination as it is popularly known) in 2006
under the leadership
of the United Nations Office for the Coordination of
Humanitarian Affairs (OCHA),
the United Nations Development Programme (UNDP), and
similar lead agencies.
This Consortium was set up to counteract the GoSL’s inability
to develop a coor-
dinated humanitarian aid structure in the District. Here, too,
local NGOs and
community-based organisations were regarded as unimportant,
and they did not
participate in the meetings. As one local NGO activist3 noted,
‘they operate in
English and conduct their meetings in Ampara town far away
from the coastal areas.
We are not important for them . . . we do not take part in this
group’. Local NGOs
have found it difficult to make their programmes effective as
their clientele is now
communally driven and preoccupied with various forms of
assistance provided by
the international NGOs. Ultimately, macro actors, such as the
Ministry of Relief,
Rehabilitation and Reconstruction (RRR Ministry), and the
departments within
it, P-TOMS, the LTTE, and the international NGOs, replaced
the bodies that took
an active interest in the early tsunami recovery process.
Due to their failure to include local networks, the aid agencies

from outside did
not have a ground-level mechanism for aid distribution. The
affected people lived
in their natural groups of kith and kin in camps, and this was
misread as ethnic
segregation and concentration. Aid distribution was organised
by the international
NGOs and other aid agencies according to those ethnically
segregated camps and
villages, and this became the new organising principle for
delivering aid. The aid
agencies were identified with the ethnicity of the camp inmates.
As a result, partici-
pation and cooperation on the part of affected communities
developed an ethnic
strand, and grew into renewed competition among ethnic groups
for tsunami aid.
The ethnocentric political ideology of the new participating
agencies, particularly the
GoSL forces, the LTTE, TRO and some international NGOs,
provided the leader-
ship for this competition.
The study’s focus and methodology
This paper examines how new developments in the humanitarian
aid distribution
process have led to a widening of the ethnic divide and
increased inequality in
Ampara District, with fisheries and housing serving as
particular examples. In doing
so, the study focuses on how tsunami aid has reached the

affected populations, and
assesses whether the aid distribution programmes were able to
provide for margin-
alised people, including the poor, vulnerable and backward
communities. These
aspects are appraised in the context of the multi-directional,
complex relationship
system that developed around tsunami aid distribution in
Ampara.
The data for this exploratory study were collected through
interviews, observa-
tions, focus group discussions and case studies. Thirty-five
interviews were held
between March and June 2006 with tsunami-affected people,
beneficiaries of tsu-
nami aid, the agencies supplying aid, key informants in the
communities, political
leaders, and members of the armed forces. The District
Livelihood Coordination
Committee of Ampara4 was a useful source. In addition,
fisheries cooperative socie-
ties offered valuable information. The armed forces in Ampara
furnished additional
information on incidents reported by the interviewees. However,
the author was un-
able to verify any of the contents of this paper with the LTTE
and the TRO.
Initially, the aid agencies were pinpointed through a list
produced by the Humani-
tarian Information Centre, Ampara (HIC, 2005) and the
Consortium for Humani tarian
Agencies–Ampara (CHA-Ampara), which was later verified by
talking to officials
from international NGOs, UNDP and the Food and Agriculture
Organization of
the United Nations (FAO) in Ampara. Secondary information

obtained through aid
agencies and the media was helpful in comprehending the
context. The triangulations
employed in the study helped to establish the authenticity,
validity and reproducibility
of the data.
Post-tsunami ethnic polarisation in Ampara
During the post-tsunami reconstruction process, ethnic
polarities resurfaced and
intensified among the Muslim and Tamil communities of
Ampara, partly due to the
failure of P-TOMS, poor recognition of local networks, and the
exclusion of local
communities from the decision-making and implementation
dimensions of the aid
delivery system. An upsurge in violence and the augmentation
of ethnic segregation
in Ampara were the results. Tsunami aid delivery thus became a
political process in
which the GoSL, the LTTE, Muslim political leaders, and
international NGOs played
the main role. The Muslim community in Ampara felt dejected
because it was not
granted adequate power and representation in the proposed
structure. What is more,
it criticised the GoSL for giving ‘undue’ power to the LTTE in
the Joint Mechanism,
despite the fact that the Muslims were the largest affected
community in the East.
Muslim leaders expressed their dismay and anger over not being

made a signatory to
the proposed P-TOMS (Rhodes, 2005).
Disagreements over the proposed institutional set-up for joint
post-tsunami recon-
struction among the GoSL, the LTTE, and the Muslim
community permeated down
to the local activities and politics of the District. Such variance
was interpreted as
reflecting ethnic differences and discrimination at the local
level. The distribution
of relief and the creation of camps occurred along ethnic lines,
reinforcing ethno-
geographic boundaries. Many incidents of ethnic rivalry were
reported afterwards,
including separate hartals5 staged by Muslims and Tamils,
highlighting the promi-
nent position of ethnic politics in post-tsunami aid distribution.
These had a negative
effect on the aid delivery system and heightened mistrust
between the communities.
A series of violent events occurred two months after the
tsunami, including:
• the killing of three Muslim men and the destruction of Tamil
barbershops in
Marathamunai;
• the killing of five Muslims during the Drawpadi Amman Kovil
festival and their
interment in Tamil burial grounds as an insult to the Muslims;
and
• the killing of a number of Tamils returning from the festival in
retaliation.
President Kumaratunga came under pressure and was forced to

appoint a com-
mission in February 2005 to investigate the murders.
The organisation of welfare camps on ethnic lines provided the
basis for various
aid agencies to select communities on ethnic grounds. The
people, Muslims and
Tamils alike, described the aid agencies that supplied assistance
as ethnically biased,
and viewed these interventions as partial, undemocratic,
wasteful, and not needs-
oriented.
Such procedures have enhanced ethnic resentment and division
between the
Muslims and Tamils, and have given an ethno-political
colouring to tsunami aid
distribution. Eventually, there were more and more instances of
aid agencies work-
ing for and among their own communities in the District,
resulting in further
distancing between the communities. Muslim politicians have
extensively utilised
the fact that Muslims were discriminated against for their own
political gain, further
aggravating ethnic consciousness. One respondent said that,
‘Muslim Congress poli
ticians headed by the minister . . . promised houses when they
win the election and
wanted us to vote for them in the election’.6
Ethnic distancing and segregation became apparent in the
ethnic concentration
of aid packaging especially that organised by the Muslims in
Colombo and outside,
which was a reaction to the failure of GoSL organisations and
international NGOs
to meet the needs of the Muslim communities. Jamathe-e-Islami

and the Muslim
Relief Foundation helped the Muslims in the area after the
tsunami. The Colombo
Mamen Society (Mamen Sangam) supported the Muslim Baithul
Tsunami (Tsunami
Fund) in Marathamunai. The Government of the United Arab
Emirates pledged to
build a new town, comprising 800 houses and modern amenities,
for tsunami-affected
people in Kalmunai. Similarly, the Government of Turkey
pledged funds for hous-
ing programmes in tsunami-affected Muslim areas. The United
States Agency for
International Development (USAID) has helped the Peace
Secretariat for the Muslims
(PSM).7 The PSM established regional centres in predominantly
Muslim areas and
assisted poor Muslim people in the communities with redressing
their grievances, with
support from USAID (USAID, 2008).
Many economic interactions between Muslims and Tamils used
to take place in
relation to land, but now it has become a politically sensitive
resource, generating
competition between the two ethnic groups. The competition is
so intense that the
LTTE has forbidden Muslims from building houses on land
located in Muslim
areas. Land-related ethnic distancing has been a factor behind
the marginalisation
of communities such as the fisher folk. They have been deprived

of the right to
their own land because of the GoSL’s policy that prohibits any
form of construction
within 65 metres of the sea, and the LTTE’s claim to all land
suitable for construc-
tion in Eastern Province.
Ethnic orientation and distancing in tsunami aid distribution
worsened over time,
because the participating agencies in the aid delivery system
took decisions and
worked spontaneously, without being subject to any central
coordination. Owing
to this lack of coordination (Stirrat, 2006), the agencies were
driven by emotional
attachments to their ethnic communities rather than by the needs
of the affected
people. As stated by the interviewees, the TRO started diverting
aid, transported
in trucks, to the North and the Tamil areas and distributing it
only to Tamils in
refugee camps. The presence of the TRO in the GoSL-controlled
areas was a result
of the Joint Mechanism, which introduced national politics to
the local scenario of
Ampara District. The intervention by the GoSL army and the
STF in aid delivery
was the result, leading to fights between the LTTE and GoSL
forces over the distri-
bution of aid. The TRO was allowed to maintain its offices in
the camps because of
the Joint Mechanism and the need to coordinate relief work.
Poor coordination and
deviations from a commonly agreed agenda between the TRO
and STF finally led
to the elimination of the TRO from the refugee camps in
Ampara. The STF inter-

vened and eventually assumed sole authority for the distribution
of humanitarian
aid in the refugee camps. Instead of facilitating the aid
distribution process, the pres-
ence of the TRO generated fear and discontent, particularly
among Tamil refugees,
as occurrences of child recruitment increased during the
post-tsunami recovery pro-
cess (Kautzky, 2005; Becker, 2005; Hindustan Times, 2005).
An incident reported at the time of the fieldwork for this paper,
which exacerbated
tension between the Muslims and the LTTE, was the decree
issued by the LTTE
on 16 April 2006 in which it stated that all females should
refrain from any form of
employment in the NGO sector (TW News, 2006). This order
was issued after a
case of abortion, alleged adult filmmaking by an unspecified
NGO, involving female
employees, and the selling of such Digital Versatile Discs
(DVDs) in the area.8 The
LTTE viewed these events as detrimental to the culture of the
Tamils (TW News,
2006). This had an effect on Muslims in Ampara because a large
number of female
Muslims, who had had to abandon their jobs because of the
tsunami, were working
in the NGO sector that sprung up in the aftermath of the
disaster. Muslims, as well
as ordinary Tamils, criticised the LTTE for prohibiting females
from working with

NGOs, as they have lost income.
There was a spate of killings and abductions of people from all
communities in the
post-tsunami environment, which also affected tsunami relief
management at the
local level in the District. The killing of the Director of the
Vocational Training
Centre (Ministry of Agriculture Marketing Development), Mr T.
Kailanathan, a Tamil,
on 4 April 2005, and the fatal shooting of the Divisional
Secretary of Thirukkovil,
Mr T. Thavaraja, another Tamil, on 15 April 2005, in
Vinayagapura, Thirukkovil,
were seen as protests against Tamils working with tsunami aid
delivery programmes
(GoSL, 2006; UTHR (J), 2005).
The power struggle between the GoSL and the LTTE over the
post-tsunami
resource (aid is seen as a resource) distribution system in the
east has terrified the
affected people, who could not effectively participate in the aid
distribution pro cess.
The instigation of the LTTE ban on the provision of land to
Muslims for house
construction was a Machiavellian move to undermine the aid
delivery process of
the GoSL and the local and international NGO sectors. The
ethnic distance between
Muslims and Tamils in Eastern Province was further widened as
a result. According
to a Tamil trader from Kalmunai:
although Marathamunai is a predominantly Muslim area, the
Tamils used to come there
before the Kovil ceremony, to a land belonging to the Kovil, to
collect poovarasu [Thespesia

populnea] trees for the ceremony. This time when they came to
collect the trees, there was
tension and fights between the local Muslims and the Tamil
visitors because of the current
situation.9
The Muslims questioned the political power of the Tamils in
the Eastern Province
in the wake of the tsunami, due to the …

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