Drrm Thesis Final Copy

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University of the Philippines National College of Public Administration and Governance Diliman, Quezon City University of the Philippines Diliman, Quezon City

Assessment and Evaluation of the Implementation of In fulfillment of the requirements inDisaster Risk The Philippine PA 199.2: Research Methods in Public Administration II Reduction and Management Act of 2010 or RA 10121in the Municipalities of Assessment and Evaluation of the Implementation of Maria Aurora and Dipaculao The Philippine Disaster Reduction and Management of 2010 in Risk the Province ofActAurora in relation to in the Municipalities of Maria Aurora and Dipaculao Community’s Knowledge in the Province of Aurora in relation to Management National College of Public Administration and Governance

Community’s Knowledge Management

PA 199.2: Research Methods in Public Administration II

Submitted by: Damazo, Frances Grace P. Submitted by: Estrella, Raymond R. Damazo, Frances Grace Nadal, Eveanne Seneca Estrella, Raymond Pagdanganan, Jasmin Y. Nadal, Eveanne Seneca Plomillo, Rea Chill C. Pagdanganan, Jasmin Plomillo, Rea Chill Submitted to: Prof. Noriel Christopher Tiglao

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ABSTRACT Natural and human-induced disasters are rampant in certain areas around the globe, especially in disaster-prone and risk-vulnerable countries. In the Philippines, where most of the provinces are susceptible to both natural and human-induced disasters, disaster risk management acquires gradually more crucial to government’s interference. This paper briefly discusses the Philippine Disaster Risk and Management Act (PDRMA) of 2010 and how it is being implemented and operationalized. After reviewing the main ideas of the PDRMA, e.g. adaptation of a holistic, comprehensive, integrated, and proactive disaster risk reduction and management approach that will eventually help lessen the socio-economic and environmental impacts of disasters including climate change, and promote the involvement and participation of all sectors and all stakeholders concerned, at all levels, especially the local community; this paper assesses the current state of the implementation and operationalization of the PDRMA in the municipalities of Maria Aurora and Dipaculao in the province of Aurora to ascertain whether the objectives of the law were successfully met in relation to Community Knowledge Management. The study will employ both quantitative and qualitative techniques in gathering the data and then will evaluate the findings in coastal and land locked areas respectively.

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ACKNOWLEDGEMENT Our group would like to extend our deepest gratitude to the following institution and people who helped in making this research study possible and successful: our parents for their unconditional love and for being our source of inspiration to pull this research off; to the local governments of Maria Aurora and Dipaculao in Aurora for uncomplainingly providing us the necessary information about the province’s DRRM programs and for determinedly helping us identify the key variables that helped us understand the subject matter even more; to the 200 respondents for sharing us their knowledge, time, effort, concerns and as well as great stories; to our thesis adviser, Professor Noriel Christopher Tiglao, for unwaveringly directing us in every step of the way and for stanchly providing us pertinent information about our research topic; to our ‘Ate’, Ms. Vivian Rose Villadolid Velasco, for solidly supporting and helping us in every way she can and truthfully, at the end of the day, we just want to make her loud and proud; to our friends, Jazelle Anne, Christine Joy, Patricia Anne, Karen, Fatima Ayesha, Mark Gil, Sigrid, Cez Martina and the rest of UP NCPAG batch 2013 for continuously giving us contagious optimism to finish this research study strong; and last, but not the least, our Almighty God for giving us spiritual strengths.

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Table of Contents Chapter 1: Introduction …………………………………………………………………….. 8 1.1 Background of the study ………………………………………………………… 8 1.2 Statement of the problem ………………………………………………………… 10 1.3 Research objectives ………………………………………………………………. 12 1.4 Significance of the study …………………………………………………………. 13 1.5 Scope and limitation ……………………………………………………………… 14 Chapter 2: Review of Related Literature ...................................................................... 15 2.1 Brief history ………………………………………………………………………. 15 2.2 Review ……………………………………………………………………………. 15 Chapter 3: Method ………………………………………………………………………….. 34 3.1 Purpose …………………………………………………………………………… 34 3.2 Paradigm ………………………………………………………………………….. 34 3.3 Study design ……………………………………………………………………… 35 3.4 Population and Sample …………………………………………………………… 37 3.5 Investigative techniques ………………………………………………………….. 39 3.6 Instrumentation …………………………………………………………………… 39 3.7 Data Collections ………………………………………………………………….. 41 3.8 Data Analysis Plan ……………………………………………………………….. 42 3.9 Ethical Consideration …………………………………………………………….. 42 3.10 Bias ……………………………………………………………………………… 43 3.11 Assumptions …………………………………………………………………….. 44 3.12 Limitations ………………………………………………………………………. 44 Chapter 4: Results and Discussions ………………………………………………………… 45 Chapter 5: Inference ………………………………………………………………………… 103 Bibliography …………………………………………………………………………………. Annex

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LIST OF TABLES 1: Data Collection Schedule 2: Case Process Summary 3: Age – Municipality Cross Tabulation 4: Age – Barangay Cross Tabulation 5: Eduation – Barangay Cross Tabulation 6: Frequency Distribution Table (FDT) – Respondents 7: FDT – Age 8: FDT – Education 9: Percentage per Municipality 10: Percentage per Barangay 11: FDT – Housing - Knowledge on the topography of land where the house is built 12: FDT – Housing - Knowledge on the over-all house safety in case of disaster 13: FDT – Housing - Knowledge on the safety of appliances/furniture at home 14: FDT – Housing - Knowledge on safety of the houses in their community in case of disaster 15: FDT – Storage - Preparedness (Emergency kits) 16: FDT – Storage - Preparedness (Emergency stocks) 17: FDT – Storage - Preparedness (Adequacy of emergency kits and stocks) 18: FDT – Storage - Preparedness (Adequacy of emergency kits, stocks & rescue equipment at the community level)

19: FDT – Shelter/Evacuation - Knowledge on the presence of the evacuation/shelter site 20: FDT – Shelter/Evacuation - Knowledge on the location of the evacuation site 21: FDT – Shelter/Evacuation - Knowledge on the safety of the evacuation site (Physical structure)

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22: FDT – Shelter/Evacuation - Knowledge on the safety of the evacuation site (Topography) 23: FDT – LGU Support - Knowledge on LGU support in case of disasters 24: FDT – LGU Support - Knowledge on suitability of LGU support in case of disasters 25: FDT – LGU Support - Knowledge LGU DRRM programs 26: FDT – LGU Support - Knowledge on the adequacy of LGU DRRM efforts 27: FDT – Community Linkage - Level of personal participation in DRRM programs of the LGU 28: FDT – Community Linkage - Level of community participation in DRRM programs of the LGU

29: FDT – Community Linkage - Community participation on DRRM issues 30: FDT – Community Linkage - Knowledge on the importance of community efforts to LGU DRRM programs 31: Materials used at home 32: Housing – Descriptive 33: Housing – Analysis of Variance (ANOVA) 34: Storage – Descriptive 35: Storage – ANOVA 36: Shelter/Evacuation – Descriptive 37: Shelter/Evacuation – ANOVA 38: LGU Support – Descriptive 39: LGU Support – ANOVA 40: Community Linkage – Descriptive 41: Community Linkage – ANOVA 42: Dipaculao Calamity Critical Routes 43: Dipaculao Evacuation Centers for each Barangay in the Municipality

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44: Dipaculao Contingency Plan on Flooding 45: Dipaculao Contingency Plan on Landslide

LIST OF FIGURES 1: National Disaster Risk Reduction and Management Framework 2: Research Structure 3: Maria Aurora and Dipaculao Maps 4: Survey Process: Designing and Integrating a Survey 5: Age Distribution per Municipality Bar Chart 6: Age Distribution per Barangay Bar Chart 7: Education per Municipality Bar Chart 8: Education per Barangay Bar Chart 9: Dipaculao’s Incident Command System 10: Hazard Map of Dipaculao for Floods 11: Hazard Map of Dipaculao for Rain-induced Landslides

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ACRONYMS

ADB – Asian Development Bank ADRC – Asian Disaster Reduction Center ANOVA – Analysis of Variance APSEMO – Albay Public Safety, Emergency and Management Office CBDRM – Community-Based Disaster Risk Management DRRM – Disaster Risk Reduction and Management FDT – Frequency Distribution Table HFA – Hyogo Framework for Action ICS – Incident Command System LGUs – Local Government Units LDRRMC – Local Disaster Risk Reduction Management Councils MDGs – Millennium Development Goals NDCC – National Disaster Coordinating Council NDRRMC – National Disaster Risk Reduction and Management Council NDRRMF – National Disaster Risk Reduction and Management Framework NGO – Non-government organization OECD – Organization for Economic Cooperation Development PHIVOLCS – Philippine Institute on Volcanology and Seismology UNESCAP – United Nations Economic and Social Commission for Asia and the Pacific

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CHAPTER I INTRODUCTION 1.1 Background of the Study The Philippines is an archipelagic country situated in the Pacific Ring of Fire. Because of its geographic location, the country is prone to almost all types of natural hazards like earthquakes, volcanic eruptions, typhoons and landslides. In addition to these natural disasters which became heightened because of Climate Change, there is also the prevalence of man-made catastrophes. It was estimated that from 1994-2003, almost 2.5 billion people were affected worldwide by natural disasters alone, with Asia as the continent most affected. Based from its geology, the Philippines is also home to three hundred (300) volcanoes, twenty-two (22) of which are active. According to the Philippine Institute on Volcanology and Seismology (PHIVOLCS), the Philippines experience an average of five (5) earthquakes per day. In addition to earthquakes and volcanic eruptions, the Philippines is also along typhoon path. In the Philippines alone, the average number of typhoons that hit the country every year is twenty (20), half of these are destructive. For the periods 1997-2007, eighty-four (84) tropical cyclones entered the Philippine Area of Responsibility which left a total of 13,155 human casualties. An estimated Php15 Billion or US $ 300 Million was spent by the Philippine Government from 1970-2000 for the annual damage brought about by these calamities. Every year the government has an estimated spending of Php 20 Billion on direct damages. A study made by the Hazard Management Unit of the World Bank in 2005 listed the Philippines as among the countries whose large percentage of its population reside in disaster prone areas. In 2011, the World Risk Report published by United 9

Nations University and the Institute of Environment and Human Security ranked the Philippines as the third most disaster risk country worldwide. Disasters, whether natural or human-made, affect everyone, especially the poor, children, women and the elderly who have the least capability to deal with disasters. (Duque, 2005) The Philippine Government, in recognition of the critical state of the country in terms of hazards and calamities, has put into place various mechanisms to address the issue at hand. The Philippine Disaster Management System is carried out by the National Disaster Risk Reduction and Management Council (NDRRMC), formerly called the National Disaster Coordinating Council (NDCC). It is under the Department of National Defense and acts as the top coordinator of disaster management in the country. Disaster Risk Management has been defined as the: systematic process of using administrative decisions, organization, operational skills and capacities to implement policies, strategies and coping capacities of the society and communities to lessen the impacts of natural hazards and related environmental and technological disasters. This comprises all forms of activities, including structural and non- structural measures to avoid (prevention) or to limit (mitigation and preparedness) adverse effects of hazards. (NDCC, 2009) In 2005, the Philippines is among the one hundred sixty-eight (168) states that adopted the Hyogo Framework for Action (HFA) which serves as a global blueprint on disaster risk reduction. In the same light, in the year 2010, RA 10121 otherwise known as the Philippine Disaster Risk Reduction and Management Act of 2010 was put into place. The act aims to strengthen institutional capacity for Disaster Risk Reduction and Management (DRRM) which

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includes local government units (LGUs), communities, vulnerable and marginalized groups. The act includes mechanisms for risk assessment and early warning, knowledge building and awareness raising, reduction of underlying risk factors, and preparedness. The act has served as a paradigm shift from having a reactive stance to a more proactive attitude towards disasters. The province of Aurora, due to its geographical location and physical environment, is considered as one of the most disaster- prone provinces in the Philippines. It is susceptible to various types of natural hazards particularly to flood and landslides. It is the northernmost province of the Southern Tagalog political division (Region IV); while it is located in the northeastern part of Central Luzon (Region III). Aurora is bounded on the north by the provinces of Isabela and Quirino, on the east by the Pacific Ocean, on the south by Bulacan and Quezon, and on the west by Nueva Ecija and Nueva Viscaya. It is generally mountainous with 30% coastal flatlands and six river drains namely the rivers of Aguang, Calabgan, Ditale, Dibatuan, Ibuna and Sinagnuan. This study focused in the municipalities of Dipaculao and Maria Aurora. Maria Aurora is the only land-locked, largest and most populous municipality in the province. It is bounded by Baler and Dipaculao on the east and San Luis on the south. On the other hand, Dipaculao is a coastal third class municipality and it is the centre point connecting the northern towns with the central municipalities.

1.2 Statement of the Problem The enactment of RA 10121 or the Philippine Risk Reduction and Management Act of 2010 has laid the ground for a more institutionalized DRRM plan. As a result, it has given local government units authority to design their DRRM plans while keeping in mind their own 11

vulnerabilities. Aurora, being one of the most calamity-prone provinces in the Philippines needs an effective operationalization of RA 10121. This research aimed to answer the following research questions: 1. How do the governments of Maria Aurora and Dipaculao implement the Philippine Disaster Risk Management Act? •

What are the existing policies or management approaches related to the implementation of the RA 10121? How is it implemented?

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Do these municipalities have the capacity to implement the said Act vis-a-viz the national standards, policies and guidelines by looking at the present conditions of the municipalities’ resources?

2. What are the present conditions of these municipalities that affect the implementation of RA 10121 in the province of Aurora? 3. What is the knowledge (perception and behavior) of the LGU on Disaster Risk Reduction and Management (DRRM)? 4. What is the knowledge (perception and behavior) of the community on DRRM? 5. Is there a difference between the knowledge of the government and the local citizens when it comes to DRRM? 6. Is there a difference in the implementation of RA 10121 between a land-locked and coastal municipality?

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7. What is the significance of the LGU and community knowledge management in the assessment of the implementation of RA 10121? 8. What are the significant experiences, setbacks and achievement the LGU and community have gained in key areas such as capacity building, community preparedness, emergency response and disaster relief recovery respectively? 9. What are the appropriate recommendations and suggested strategies that may help the Municipality of Dipaculao and Maria Aurora in implementing RA 10121?

1.3 Research Objectives This study aimed to assess and evaluate the implementation of RA 10121 or known as the Philippine Risk Reduction and Management Act of 2010 in the province of Aurora particularly looking at the municipalities of Maria Aurora and Dipaculao through community knowledge management. This research has the following objectives: •

Assess the present capacity of the municipalities of Maria Aurora and Dipaculao in implementing RA 10121 through community knowledge management  Analyzing the budget of the LGU for RA 10121  Evaluating existing policies  Evaluating

the coordination of the LGU with various internal and external

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 Identifying the gaps among policies and arrangements •

Identify the significance of knowledge management in the assessment of the implementation of RA 10121

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Identify the community’s knowledge management on disaster risk reduction and preparedness

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Identify the difference of the implementation of RA 10121 between a landlocked and coastal municipality based on the community’s knowledge management

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Identify the gap between the LGU and community’s knowledge management on the implementation of RA 10121

1.4 Significance of the Study Given the vulnerabilities that the Philippines are exposed to, a proper implementation and operationalization of Disaster Risk Reduction and Management is needed. Because of the country’s geographic location, there is a great need to institutionalize and strengthen local governments and equip them with the proper knowledge, skills and resources for DRRM. The province of Aurora is identified to be one of the most exposed to calamities because of its topography Consequently, the huge damage induced by natural disasters on the locality, particularly on its people and property runs into billions of pesos. And unfortunately, the effects fall worse on the poor and on areas which have low level in growth and development. On the other hand, it is fortunate that local officials, together with the national government and other institutions, are aware of the problem and initiate in building local capacities for disaster risk reduction and 14

management. The Republic Act 10121 calls for the capacity of the local government among its government personnel, local people and other stakeholders for early recovery and rehabilitation of affected people and areas. The study of the problem offered a wide-range assessment of the recognition of appropriate policies and institutional framework in dealing with natural disasters and climate change by looking into knowledge of the government and the local citizens. The problem also called for the development of policies and plans that will lessen socio- economic and environmental impacts of disasters and will promote the involvement and participation of all sectors and stakeholders at the local level. 1.5 Scope and Limitation The researchers studied the province of Aurora, with focus on its most vulnerable municipalities, specifically in Maria Aurora and Dipaculao and see how these municipalities operationalize the Philippine Disaster Risk and Management Act of 2010 through community knowledge management. The researchers looked at the effectiveness of the implementation of RA 10121 on the said municipalities. Moreover, it reviewed and assessed the various existing capacity development initiatives and practices of the localities. It also identified and analyzed current capacity building efforts and gaps in the operation of the Disaster Risk Reduction and Management. The study gathered primary data through conducting focus group discussions with key informants who are knowledgeable of the topic at hand and are hands-on in implementing the Act. In addition, to provide a deeper understanding of the study, supplementary data is drawn from various analyses and reviews of annual reports and other literature. 15

CHAPTER II REVIEW OF RELATED LITERATURE 2.1 Brief history The Philippines is one of the most disaster-prone countries in the world. It is located in South-eastern Asia, an archipelago between the Philippine Sea and the South China Sea. It is very prone to natural hazards such as astride typhoon belt, usually affected by 15 and struck by five to six cyclonic storms each year; landslides; active volcanoes; destructive earthquakes; tsunamis (CIA, 2012) Presently, the world is faced with the threat of the atypical change of climate which leads to disasters and has fetched apprehensions to the different countries in the world especially those countries located in disaster prone areas of the globe. These issues have obviously called the attention of national government. Different interventions have been formulated to address the issue on Disaster Risk Management in the country. The Philippine Disaster Risk Reduction and Management Act of 2010 is one of the most primary and significant mechanisms to strengthen the disaster risk management in the country by providing the national framework and management plan. 2.2 Review This study was conducted to assess and evaluates the implementation of Philippine Disaster Risk Management of 2010 (RA 10121) in the municipalities of Maria Aurora and Dipaculao in the province of Aurora in relation to its Citizen’s Perception and Behaviour. The 16

related topics to be discussed are divided into two: local and foreign studies. The local studies are Philippine Disaster Risk Reduction and Management Act of 2010, National Disaster Risk Reduction and Management Framework (NDRRMF), Monitoring and Reporting Progress on Community-Based Disaster Risk Management in the Philippines, and Innovative Humanitarian Response within a Disaster Risk Reduction Approach: "Learning from the 2009 Mayon volcano Eruption, presented how Albay province attained a "Zero Casualty. Moreover, the foreign studies include Risk, Vulnerability and Asset-based Approach to Disaster Risk Management (Krishna Vatsa, 2004), Disaster Risk Management in Southeast Asia: A Developmental Approach (Benjamin Loh, 2005), Disaster Reconstruction and Risk Management for Poverty Reduction (Margaret Arnold, 2006), Japan’s Jishu-bosai-soshiki community activities: analysis of its role in participatory community disaster risk management (Robert Bajek et.al., 2007), Community Diagnosis for Sustainable Disaster Preparedness (Matsuda et.al., 2006) and Disaster Risk Management in a Global World (Pranee Chitakornkijsil, 2010) The aforementioned studies are relevant to our research studies because they fully delved into the root causes of the problem and suggested different ways on how to solve the main problem – Disaster Vulnerability. Also, the measures applied in the studies adapted to the geographical features of the countries involved. Philippine Disaster Risk Reduction and Management Act of 2010 Former President Gloria Macapagal-Arroyo signed the Republic Act 10121 or the Philippine Disaster Risk Reduction Management Act of 2010 which would primarily reorganize the National Disaster Coordinating Council (NDCC) The law recognized the need to “adopt a 17

disaster risk reduction and management approach that is holistic, comprehensive, integrated, and proactive in lessening the socio-economic and environmental impacts of disasters including climate change, and promote the involvement and participation of all sectors and all stakeholders concerned, at all levels, especially the local community.” “This Act provides for the development of policies and plans and the implementation of actions and measures pertaining to all aspects of disaster risk reduction and management, including good governance, risk assessment and early warning, knowledge building and awareness raising, reducing underlying risk factors, and preparedness for effective response and early recovery,” according to the law. The NDCC has been renamed and now called the National Disaster Risk Reduction and Management Council (NDRMC). It is primarily empowered with policy-making, coordination, integration, supervision, monitoring and evaluation functions. One of the most important functions of NDRMC is the development of a national disaster risk reduction and management framework, which shall provide for comprehensive, all-hazards, multi-sectoral, inter-agency and community-based approach to disaster risk reduction and management. At the local level, Barangay disaster coordinating councils are now abolished and its functions have been transferred to the local disaster risk reduction management councils (LDRRMC). LDRRMC is mainly responsible to endure the integration of disaster risk reduction and climate change adaptation into local development plans, programs and budgets as a strategy in sustainable development and poverty reduction. RA 10121 is aimed to mainstream disaster risk reduction and climate change in development processes such as policy formulation, socio-economic development planning, 18

budgeting, and governance, particularly in the areas of environment, agriculture, water, energy, health, education, poverty reduction, land-use and urban planning, and public infrastructure and housing and for the integration of disaster risk reduction education into the school curricula and Sangguniang Kabataan program and mandatory training for public sector employees. It can also be employed for relief, recovery, reconstruction and other work or services in connection with natural or human-induced calamities, which may occur during the budget year or those that occurred in the past two years from the budget year. Thirty percent of the overall appropriated fund for NDRRM shall be allocated as Quick Response Fund or standby fund for relief and recovery programs in order that living conditions of people in communities or areas stricken by disasters, calamities, epidemics, or complex emergencies, may be normalized as quickly as possible (Marvin Sy, 2010) National Disaster Risk Reduction and Management Framework (NDRRMF) The Disaster Risk Reduction and Management Framework aims to elevate awareness and understanding among the national government, local governments and the people on the country’s DRRM goal. A national framework for DRRM is essential to guide national and local efforts in DRRM because it provides the overall set of priorities and delineates the fundamental elements and components of disaster risk reduction and disaster risk management in the country. The DRMM framework is designed to provide common direction towards addressing underlying causes of vulnerability to help reduce and manage the risks to disasters. The DRRM framework will also show the DRR and DRM efforts are inevitably linked to the development process and not just merely set of activities and should come together and contribute towards attaining sustainable development.

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The NDRRM Framework is together a set of criteria for the benchmarking the effectiveness of disaster risk reduction measures and a tool for monitoring and evaluating the progress. Chiefly, the Framework provides a basis for political advocacy as well as practical action and implementation. It also emphasizes the areas where capacities need to be developed and provide a basis for setting goals, objectives and targets adapted to various circumstances, against which progress can be measured and gaps identified. The Philippine National DRRM Framework is an important component to ensure the country’s sustainable development as an essential part of the development process. Clearly, its success relies heavily on strongly supported national ownership and leadership of the DRR process. This national framework is based on the subsequent principles on disaster risk reduction and disaster risk management or DRRM: it is about addressing the underlying causes of vulnerability; it is a national responsibility within a sustainable development approach; it stresses the need for community empowerment and shared responsibilities; it is about good responsive governance and mutually reinforcing partnerships; it needs strong and responsive political will, commitment and leadership; and it is best done through local and customized adoption (and adaption). (National Disaster Risk Reduction and Management Framework, 2011) Figure 1. National Disaster Risk Reduction and Management Framework

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Monitoring and Reporting Progress on Community-Based Disaster Risk Management in the Philippines The National Disaster Coordinating Council (NDCC) undertook a collaborative project entitled “Learning for Good Practices: Case Study on Community-Based Disaster Risk Management in the Philippines.” One of the activities was spearheaded by Oxfam Great Britain and last August 10, 2007, the Workshop on the Selection Criteria for Community-Based Disaster Risk Management Case Studies was conducted. Representatives from NGOs and national government agencies identified the following key elements of CBDRM: (1) Community Ownership, (2) Use of Local Knowledge about Hazards, (3) Communities as Ultimate Beneficiaries, (4) Multi-stakeholder Participation, (5) Education and Capacity Building, (6) Gender Sensitivity, (7) Cultural Appropriateness, (8) Sensitivity to Local Structures, (9) Harmonization of Local, Indigenous, and Scientific Knowledge, (10) Complementation

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Community-based and Top-down approaches, (11) Demonstrated Potential for Building Economic Resilience, (12) Demonstrated Transparency in Procedures and Processes, (13) Commitment and Accountability of Stakeholders, (14) Communication Design and (15) Exit Strategy (sustainability mechanism).

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At the national level, Asian Disaster Preparedness Center is among the several International NGOs collaborating with the NDCC/OCD on various CBDRM projects and programs. Another international organization is the Oxfam Great Britain that supports NDCC’s CBDRM thrust which collaborated with NDCC’s “Learning from Good Practices: Case Studies on Community-Based Disaster Risk Management in the Philippines”.At the local level, there are international and local non-government organizations that have implemented CBDRM-related activities in 55 provinces and cities, 43 are identified as at-risk provinces and targeted by the READY project. In 2005, the first 27 provinces identified are Benguet, Abra, Ilocos Norte, Ilocos Sur, Cagayan Valley, Isabela, Nueva Viscaya, Quirino, Pampanga, Zambales, Aurora, Cavite, Laguna, Rizal, Catanduanes, Antique, Iloilo, Bohol, Leyte, Southern Leyte, Eastern Samar, Northern Samar, Zamboanga del Sur, Zamboanga Sibugay, Agusan del Sur, Surigao del Norte, and Surigao del Sur. And in 2007, the next 16 provinces were identified with specific target cities or municipalities and these are Cebu (Metro Cebu), Pangasinan (Dagupan City), Bulacan (Dona Remedios Trinidad and San Miguel), Agusan del Norte (Butuan City), Camarines Norte (Daet), Quezon (Lopez-Caluag), Oriental Mindoro (Calapan), Aklan (Kalibo), Batanes (Basco), Zamboanga del Norte (Dipolog City, Bukidnon (Malaybalay City), Davao Oriental (Mati), Mountain Province (Bontoc), and Lanao del Sur (Malabang). At present, the READY Project has been implemented in nine (9) of the identified at-risk provinces, namely: Benguet, Cavite, Pampanga, Aurora, Bohol, Leyte, Southern Leyte, Surigao Del Norte, and Surigao Del Sur. This number comprises 21 percent of the total identified at-risk provinces. Most of the CBDRM activities in the Philippines are framed on a holistic approach to disaster preparedness and mitigation and not just merely on disaster preparedness and mitigation 22

measures. The combination of activities in disaster preparedness and mitigation has been aptly called as disaster risk reduction (DRR). In the Philippines, NGO activities are gearing towards the concept of DRR as an approach to CBDRM, which covers both humanitarian action and socio-economic development activities. Furthermore, there appears to be a wide recognition that disasters can be reduced or prevented by enhancing the capabilities of at-risk groups or communities to cope with hazards or disasters and resist its impact on them. (Monitoring and Reporting Progress on CommunityBased Disaster Risk Management in the Philippines, 2008).

Innovative Humanitarian Response within a Disaster Risk Reduction Approach: "Learning from the 2009 Mayon volcano Eruption, presented how Albay province attained a "Zero Casualty" In the course of the institutionalization of the Albay Public Safety, Emergency and Management Office (APSEMO) the province has achieved the "Zero Casualty" goal during Mt. Mayon eruptions in 2001, 2006 and 2009. The province DRRM had an effective and efficient system in monitoring and evaluation in implementing disaster operation, back up with adequate logistical and legislative policy support. The study also credited the APSEMO's DRM model for making the province become a landmark of and a voice in the international discourse of DRM. With the DRRM the province was able to institutionalize disaster responses within the risk management framework designed to build a resilient and safe community towards sustainable development.

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According to Albay Gov. Joey Salceda, “DRR model institutionalized by the province is an innovation where in stakeholders where put together working for a common cause”. Snehal Soneji, Oxfam Country Director was impressed of Albay's DRRM model saying "this is a unique model where you can see how partnership played a great role in disaster operation." "I have seen other models but the uniqueness of Albay's DRRM is the partnership and innovation made in performing its respective task," Soneji said. Cedric Daep, APSEMO director said the research study was a follow up of the first DRR study made and subsequently published last year entitled "Building a resilient DRR." (Philippine Information Agency, 2010) Risk, Vulnerability and Asset-based Approach to Disaster Risk Management The impacts of disasters across the globe are unevenly distributed. Vulnerability is the key factor which explains how risk outcome is spread across the households. It is fundamental to disaggregate the impact of disasters on people, on their habitats and livelihoods to understand how households and communities are affected by disasters. The paper suggests that the probability of being affected by disasters depends upon (1) the frequency and severity of the impact and (2) the people’s resilience to a given shock. Social class generally marks people’s capacity to cope and recover. Oftentimes, the poor and the vulnerable sector are left open to disasters and risks. The low- income people find it difficult to recover after disaster due to lack of financial resources and technical skills. While the upper and middle classes recover faster from a disaster through the help of stable employment, insurance and assets. These assets are the means of resistance that households can mobilize when fronted with calamities. Assets play a central role in reducing

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vulnerability. It covers the stock of wealth (tangible and intangible) in a household. The vulnerability of a household can be determined by its asset endowment, like welfare losses and risk management strategy. While access through financial resources can help households recover from disasters, social protection measures like housing can help reduce the risk of floods and earthquakes. The government should be effective in implementing such safety net strategies and encourage the sharing of information among communities and building of networks (Vatsa, Krishna S) Disaster Risk Management in Southeast Asia: A Developmental Approach According to the report of UNESCAP and the Asian Development Bank (ADB) in the year 2000, about 75% of the world’s major natural catastrophes between 1970-1997 occurred in the Asia-Pacific Region, with most poverty-ridden countries as those gravely affected. Oliver Smith (1999) suggested that in most disaster examination, time was reduced to a relatively shallow duration in which only conditions immediately prior to the calamity were probed and only individual, group, and societal behavior in moments of threat or short-term aftermath was explored. Indeed it has been observed that the dominant response and action on response action on disaster management in Southeast Asia had been on post-disaster activities and particularly on emergency response. (Bildan 2003;Jegillos 2003) Gurenko (2004), however, identified different drawbacks from this kind of postemergency reconstruction. First, it is reactive by nature. Because of this, it provides little incentive for countries to engage in active risk management to reduce their vulnerabilities to natural disasters before they occur. Disaster-prone countries are unprepared to deal with the devastating consequences of natural catastrophes when they occur. The main thrust of government is likely to be focused on the physical reconstruction of destroyed assets, with little 25

attention paid to the development of forward-looking catastrophe risk- management solutions. Second, even when multinational development banks and donor agencies can finance a significant percentage of government reconstruction work in the aftermath of natural disasters, the funding comes with a significant delay, jeopardizing government efforts. At the end, postemergency lending tends to produce little visible improvement in countries’ economic and fiscal vulnerabilities to future natural disasters, leaves countries with higher debt burdens, and dampens the incentives for active, forward-looking risk management. The heart of a country’s strategy for managing disaster risk should not be loss-financing. Instead, it should be development-enhancing to optimize post-loss funding capacity and budgetary discipline to protect and sustain current and future development projects. (Benjamin, 2005) A major consequence of this is that modeling in many countries is very dependent on expert opinion, and extrapolation from developed world models (Walker 2004; Evers and Menkhoff 2004) As a result, the models may not be completely relevant. Walker (2004) suggested that a solution was to foster local public-research-based activities with the objective of producing national standard assumptions for modeling vulnerability and hazard risk, which could be used freely by any disaster modellers. This means that it is based on local costs. As a result local researchers have the ownership of local disaster management models, which serves as driving force for the continual upgrading of the models. (Benjamin, 2005) Walker (2004) further notes that there is a need to establish or strengthen institutional frameworks for disaster preparedness and mitigation at national, regional, district and community levels.

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Mitigation measures can be of different kinds, ranging from physical measures such as flood defenses or safe building design, to legislation, training, and public awareness. Mitigation is an activity which can take place at any time: before a disaster occurs; during an emergency; or after a disaster, during recovery or reconstruction. (Benjamin, 2005)

Disaster Risk Management and Poverty Disaster risk management, as defined by the Asian Disaster Reduction Center (ADRC), is the systematic management of administrative decisions, organization, operational skills and capacities to implement policies, strategies and coping capacities of the society and communities to lessen the impacts of natural hazards and related environmental and technological disasters. This comprises all forms of activities, including structural and non-structural measures to avoid (prevention) or to limit (mitigation and preparedness) adverse effects of hazards. The disaster experienced by the United States in 2005 brought about by the hurricane Katrina serves as a reminder that any city or country, no matter how rich or abundant it is, can be caught unprepared for disaster. It also reminds us of the level of poverty that exists in parts of one of the world's wealthiest nations.

Natural disasters are a major source of risk for poor people. However, this vulnerability also happens to be one of the most overlooked dimensions of poverty. One possible reason is that disasters have traditionally been considered a humanitarian assistance issue rather than one

27

of development. Relief and development were viewed as two different "industries" with very separate mandates, actors and sources of funds.

This shows that there is an undeniable link between poverty and the impacts of disasters. The main reason why the disaster risk management is an integral part of the World Bank’s mission — the Millennium Development Goals (MDGs) — to fight poverty. To achieve the MDGs, the disaster risk reduction must also be addressed. The World Bank, as the largest provider of reconstruction and development assistance, bears a responsibility to promote a more developmental approach to reducing disaster risk. The World Bank established a central unit, the Hazard Risk Management team (formerly called the Disaster Management Facility) to focus on disaster risk management in 1998 which changed this conception of being an “orphan sector”. The unit's objectives are to facilitate a more strategic response to disaster emergencies and to enhance the World Bank's poverty alleviation efforts by integrating effective disaster risk reduction into development activities. The World Bank worked and extracted lessons with external partners to tap into the wide array of disaster risk management expertise around the globe and to improve its disaster emergency response. This was done through the ProVention Consortium which was launched in 2000. It is a global coalition of governments, international organizations, academic institutions, the private sector and civil society organization dedicated to increasing the safety of vulnerable communities and to reducing the impact of disasters in developing countries focusing on relief, recovery and development. Current World Bank policy is very clear that it is not a relief organization, but rather supports the restoration of "assets and production levels in the disrupted economy." 28

For relief, the World Bank’s direct support for community subsistence is through mechanisms such as cash payments, food or cash for work programs. However, the World Bank's

policy

on

financing

cash

payments

has

been

waived

many

times

and

recent reconstruction projects increasingly include livelihoods components. World Bank policy on emergency lending is currently under revision, and the new policy will likely incorporate this change. Another major feature of the World Bank’s relief programs is housing reconstruction, a top priority for disaster-affected communities. However, this relief program is quite problematic in terms of viability due to incidence of incomplete or sub-standard housing projects.

In Margarette Arnold’s Reconstruction and Risk Management for Poverty Reduction, she stated that the promotion of gender equality is another important area that can often be addressed easily and speedily in the recovery process. Recovery programs also need to be pro-poor and can be able to provide an effective vehicle for poverty reduction given that natural disasters have wide-reaching impacts and since the poor are the hardest hit by disasters. The newer disaster recovery projects prepared by the World Bank have an increasing focus on supporting the livelihoods of the poor, unfortunately the impact of recovery programs on the poor has not been systematically tracked and needs more quantitative analysis.

Mainstreaming disaster risk management into development requires the incorporation of hazard risks into policy frameworks, and allocating the necessary resources to manage those risks. It also requires an understanding of the relationship between poverty and disasters, and how they reinforce each other. From a practical point of view, there is clearly a need for both top-down and bottom-up approaches in reducing disaster impacts in developing countries.

29

For its part, the World Bank is increasing efforts on a number of fronts to manage disaster risk in a more proactive way through working with partners to develop tools and training for mainstreaming disaster risk into design and implementation of investments. It is working with several partners to identify global disaster risk "hotspots" in order to inform the development planning efforts of aid agencies and governments. The World Bank is also exploring more efficient and effective mechanisms for financing disaster risk.

Much more remains to be done, and each actor has a critical role to play. More donors, civil society actors and governments need to shift from a reactive to a preventative approach in order to protect lives and avoid losses. The technologies for risk reduction are well-known and must be applied. We also need to better acknowledge the global economic forces that contribute to the vulnerability of the poor, and strengthen local capacity for managing risk. At the national and international levels, we need to find the right incentives and rewards for effective risk management, as there is still too much to gain politically, both for donors and governments, from making disaster response an apparent aspect of the development agenda. Until this happens, the cycle will continue, and disasters will continue to widen the gap between rich and poorseemingly, but erroneously, with no one but nature to blame.

Participatory disaster-risk governance in Japan In Japan, disaster risk management starts at the community-level. The government established links with the local citizens’ associations like Jishubo which plays a crucial role in participatory disaster risk in Japan. Jishu-bosai-soshiki, or Jishubo for short, literally means ‘‘autonomous organization for disaster reduction’’ is a neighborhood association for disaster preparedness and rescue activity at the community level in Japan. (Bajek, Matsuda and Okada, 30

2007). In this strategy, the Chonaikai, a traditional Japanese community governance system, is incorporated to the disaster risk framework to mobilize households to participate in disaster risk workshops and trainings. Jishubo members organize disaster drills, educate residents, patrol their residential area and maintain rescue tools during normal times and guide refugees to a shelter, rescue residents, provide the initial first-aid and supply food and water during emergencies. This implies that the decision-making and responsibility during emergencies is vested on the residents. However, in reality, local governments provide a subsidy for purchasing emergency foods and rescue tools to encourage residents to participate in the Jishubo system. The theory behind the central and local government fostering the Jishubo system is grounded on the “Basic Law on Natural Disasters”. This was brought about by the 1995 Kobe earthquake where community-based disaster risk was found to be important. Since then, the government started promoting Jishubo under slogans such as ‘‘Mutual assistance is necessary since the public rescue service is not perfect.’’ and ‘‘Community linkage saves lives in an emergency” (Bajek, et.al, 2007). Another theory that this framework emphasized is the ‘‘Fairness and Competence’’ theory of participatory management (Renn et al. 1995), which was primarily been implemented in the field of environmental management. According to this theory, Fairness should characterize participatory processes such that every person interested in the issue at stake should be given an equal opportunity to take an active part in the participatory process. Every person should also have some manner of influencing the agenda and rule-making as well as participating in moderation and discussion of the decisions.

31

The increasing number of Jishubo households showed that mobilized participation seems to work by instilling a sense of belongingness among its member households. This was proven in a study conducted by Bajek et al. (2007) in Kishiwada, Osaka, where they found that member participatory motivation in workshops and trainings did not necessarily rely on perceived practical use of knowledge from workshops but on the sense of belonging to the group by being treated as a partner, even though their influence to the participatory process is limited. The incorporation of the traditional Chonaikai to the Jishubo system also contributed to the effectivity of the participatory process. The Chonaikai has long served as an institution to transmit and implement policy awareness and dissemination among residents. Despite being influenced by new streams of governance, the Chonaikai community governance unit is still very sound and stable, and thus indispensable in community governance. There is an assertion, therefore, that attitude of members are more passive rather than proactive, such that their motivation to join activities are not derived from their interest on disaster risk management but instead from their obligation and subordination toward their Chonaikai leader.

Community Diagnosis for Sustainable Disaster Preparedness The paper focuses on Community Diagnosis method which deals with the need for sustainable disaster preparedness at the community level with the help of the disaster experts and key person involved. Disaster preparedness is viewed as a participatory community management process, where all key stakeholders are expected and needed to share knowledge. Knowledge creation model is classified into two phases: knowledge externalization and knowledge combination.

32

Knowledge externalization is designed as a diagnostic survey to determine the need to be checked of a particular community; it uses survey questionnaire. On the other hand, Knowledge combination is designed as a prescriptive workshop for the citizens and community officials to enhance community preparedness through face-to-face communication. The Knowledge externalization is aimed at collecting knowledge directly to the people concerned using different instrument such as survey questionnaire while Knowledge combination is the integration of the key stakeholder’s familiarity about community disaster preparedness. Okada et.al, 2001 defined “community diagnosis” as a tool to externalize tacit knowledge (including ideas, opinions and attitudes) about common space related social problems. The paper discussed the ongoing research of community diagnosis for disaster preparedness.

Disaster Risk Management in a Global World The study identified the disasters and crisis factors and as well as the various international risks and risk management perspective including emerging international risks in a global context. It also discussed the domestic crisis management as an augmented international activity and considered international crises and their role in potential domestic threats. The study identified the disasters and crisis factors and as well as the various international risks and risk management perspective including emerging international risks in a

33

global context. It also discussed the domestic crisis management as an augmented international activity and considered international crises and their role in potential domestic threats. Risk Management is defined as the process of identifying, treating, and evaluating risk can be applied to enhance the success of new projects, assist organizations in accomplishing their objectives, and to ensure continued service should a crisis occur. It is a complex process that is influenced by the specific cultural, political, economic, and social circumstances of the country. Geographical location can determine whether loss or damage from tornadoes, hurricanes, drought, flood, forest fires, or tsunami is possible. Cultural and ethical factors can influence the nature and the application of bribes necessary in some countries in order to obtain services or gain certain permissions from the public sector. The political and economic situation may encourage theft for political and financial gain by disaffected groups, which poses a particularly higher risk for employees working overseas. Religious and political problems may cause war, terrorist activity, and general unrest. There is an emerging International Risk and the nature of risk is always changing. Emerging risks are phenomena whose effects and nature cannot even be guessed at in term of loss within a specified time period. And emerging risks have significant impacts. Five large and serious threats have been identified: technological accidents, natural disasters, terrorism-related risk, food safety, and infectious diseases. The OECD proposes four critical contexts that are related to management of emerging risks: demography, environment, technology and socioeconomic structures. Conclusion

34

The significance and call for a holistic disaster risk management in the Philippines can be emphasized more in these studies. Nevertheless, in the aforementioned discussions, for the program or a law to effectively impact its recipients, not only must the disaster risk management law or different mechanisms, but also to provide effective and useful mechanisms that allow the people to actively participate and the government to aggressively respond to the needs of the people especially those who live in disaster-prone areas. Furthermore, the disaster risk management mechanisms must aim for a strong government-citizen relationship.

CHAPTER III METHODOLOGY 3.1 Purpose The primary purpose of this study is to assess and evaluate the implementation of the Philippine Disaster Risk Reduction and Management (DRRM) Act (R.A. 10121) in the municipalities of Maria Aurora and Dipaculao in the Province of Aurora in relation to community knowledge management. The researchers aim to identify the present efforts of the Local Government Unit and evaluate the degree of congruence and effectiveness of these efforts with specific provisions in the Philippine Disaster Risk Reduction and Management Act while taking into consideration the community’s knowledge in relation to it. 3.2 Paradigm

35

Disaster Risk Reduction and Management in the Philippines is the result of a paradigm shift from a purely disaster response approach into a humanitarian, relied and response approach. The latter was brought into public policy application due to scientific and technological innovations that made possible the forecasting and modeling of natural hazards such as earthquake and floods, thus reducing the impact of natural hazards to humans. These lead to the channeling of resources into hazards education, disaster risk reduction and management trainings, humanitarian assistance, disaster aid, and relief operations. These efforts, together with the aggregate of other efforts designed to adapt to weather and socio-political conditions, were formalized into one comprehensive law on Disaster Risk Reduction and Management.

For the purposes of this study, the researchers primarily used the Structural Functionalist approach to explore how the municipalities of Maria Aurora and Dipaculao in the Province of Aurora comply with the current framework of the Philippine National Disaster Risk Reduction and Management. In consistent with the provisions of the R.A. 10121, the researchers gauge how far the paradigm shift have decentralized its efforts to local public administration. The researchers also looked into the functions and efforts of the provincial and municipal government and the residents of the municipalities and how these different sectors contribute to the implementation of the Philippine Disaster Risk Reduction and Management Act. 3.3 Study Design The researchers are doing an exploratory study with a mixed method approach by using both qualitative and quantitative method for the research. Mixed method research is formally defined as the class of research “where the researcher mixes or combines quantitative and

36

qualitative research techniques, methods, approaches, concepts or language into a single study” (Johnson & Onwuegbuzie 2004: 17). The rationale for mixing is that neither quantitative nor qualitative methods are sufficient by themselves to capture the details and information needed to study both the dependent and independent variables identified in this study to answer the research questions. This also allows the employment of more techniques to be able to convey a more in-depth account of the phenomenon being studied. When used in combination, quantitative and qualitative methods complement each other and allow for more complete analysis (Green, Caracelli, & Graham, 1989, Tashakkori & Teddlie, 1998)

Figure 2. Research Structure

37

3.4 Population and Sample

38

The sample population the researchers interviewed for the interviewer-administered survey are people from the municipalities of Maria Aurora and Dipaculao in the province of Aurora. The sample population is aging from 15 years and above. There are 200 respondents in the sample population with 100 respondents from the municipality of Dipaculao and the other 100 from the municipality of Maria Aurora. The 100 participants from each municipality are taken from 3 barangays, having 34, 33 and 33 respondents from each barangay. The barangays in the municipality of Maria Aurora are Diome, Sta. Lucia, and Cabituculan. In the municipality of Dipaculao, the barangays are Salay, Dinadiawan, and Ipil. For the interview, the researchers interviewed a population of 1 to 2 officers each from the local government units (LGUs) of the two municipalities. The sampling plan the researchers used is the purposive sampling. Purposive sampling is a form of non-probability sampling in which decisions concerning the individuals to be included in the sample are taken by the researcher, based upon a variety of criteria which may include specialist knowledge of the research issue, or capacity and willingness to participate in the research. Some types of research design necessitate researchers taking a decision about the individual participants who would be most likely to contribute appropriate data, both in terms of relevance and depth. The researchers also used purposive sampling because there are specific and limited people who are qualified to be the respondents for the research study. Since the study only needs survey respondents from the two municipalities, Maria Aurora and Dipaculao, the researchers limited the sample to these places; for the interview, the researchers will need 1 to 2 officials or

39

people who have knowledge and authority in the LGUs in the two municipalities to be interviewed. Figure 3. Maria Aurora and Dipaculao Maps

40

3.5 Instrumentation and Investigative Techniques For this study, the researchers collected data by using an interviewer-administered survey questionnaire and interviewing as their investigative techniques. The researchers designed and implemented a survey by following a systematic process of gathering information on a specific topic by asking questions to individuals and then generalizing the results to the groups represented by the respondents. Figure 4. Survey Process: Designing and Implementing a Survey

The questionnaires have structured questions with a formal list of questions asked to all respondents in the same way with a direct approach. The structured questions for the collection of data constitute both open and closed-ended type. For the survey questionnaire, questions that can be rated from a scale of 1 to 10 were structured and open-ended questions for the interview. The questions from the survey questionnaire are mostly self-evaluation questions. The set of questions asks a respondent to evaluate their self and their community’s preparedness for disasters, specifically for floods and landslides on a scale of 1 to 10. The questions are divided into five indicators: Housing, Shelter, Storage, LGU support and Community linkage. The response for each question is converted to a score with a scoring system of a 3-point scale questions. 3-point scale questions are scored 1, 5 or 10, depending on the respondent’s choice. A rating between 1 to 3 is scored as 1 and is classified as “not aware”, a rating between 4 to 7 is

41

scored as 5 and is classified as “fairly aware”, and a rating between 8 to 10 is scored as 10 and is classified as “very aware”. The open-ended questions on the other hand, are those that allow respondents to write in or speak their answer freely, without having to choose a predetermined response category. The researchers used structured interviews with open-ended questions for gathering data from the officials in the LGUs. This involves questions which are set out and followed thoroughly. Secondary

data will also be collected

as

an

investigative

technique

to augment

the studies. Before the actual data collection from the citizens and officials, the researchers collected data from the province’s official website and other studies conducted to gain more information and knowledge for the study. The independent variables the researchers identified for this study are: (1) Status of national and provincial DRRM and (2) Community Knowledge Management on DRRM. For the dependent variables, the researchers identified are: (1) Relationship between statutory provisions and actual implementation and (2) Level of knowledge (perception, preparedness and participation) of citizens on DRRM strategies, programs and issues at individual and community levels. For these variables, the levels of measurement the researchers used are nominal and scale. At the nominal level of measurement, numbers or other symbols are assigned to a set of categories for the purpose of naming, labeling, or classifying the observations. The scale level of measurement is used in the survey questionnaire where the respondents’ answers are rated in a

42

scale of 1 to 10. These levels of measurement are important especially because the researchers used survey and interview as their investigative technique. 3.6 Data Collections The research instrument the researchers used, interviewer and researcher-administered survey questionnaires, are distributed in the households in the two municipalities identified. The researchers distributed this house to house or by personally visiting the households in these municipalities that are prone to disasters such as flood and landslide. And because the respondents will be guided by the researchers while they are answering the questionnaires, the instruments were accomplished on the same day. The timetable for data collection is shown in Table 1. Table 1. Data Collection Schedule

Day 1 to

•

Day 2 •

Week 1 Interview officials from the

•

Participants 1 to 2 officials from the LGU

municipality of Dipaculao

•

100

Administer households

survey in

the

respondents

from

the

in

Municipality; 33 to 34 respondents

3

from each of the 3 barangays

barangays of the municipality Day 3 to

•

of Dipaculao Interview officials from the

•

1 to 2 officials from the LGU

•

100

municipality of Maria Aurora

Day 4 •

Administer households

survey in

the

in 3

barangays of the municipality

respondents

from

the

Municipality; 33 to 34 respondents each from 3 barangays

of Maria Aurora

43

3.7 Data Analysis Plan For the data analysis, the researchers used both univariate or descriptive statistics and inferential statistics to analyze their data. Univariate data analysis is the analysis of a single variable as opposed to conducting data analysis using two or more variables. The term “descriptive statistics” is most often associated with summarizing the characteristics of a variable or a set of variables. For the levels of measurement, a measure of central tendency is used as a reference to the statistical procedures associated with describing the distribution of values of the responses to a single variable. This includes the mode, median, and mean. Other information about the distribution of scores in a variable that further assist with describing the variable include the range, upper and lower limits, variance, standard deviation, and confidence interval. Generally, for the data analysis, the researchers will use a qualitative analysis of data, interpretation of interviews, content analysis and descriptive analysis, and quantitative analysis, to be able to present the summary data. 3.8 Ethical Consideration There were no major ethical issues in the research study. The methods of the study did not incorporate complicated techniques of data gathering that might result to violation of the ethical standards of research. The researchers did not need to deceive respondents regarding any part of the study; the researchers informed the participants of the objectives of the study they are participating in.

44

In conducting the study, the researchers has employed the basic elements of informed consent.This involves providing each respondent a consent form explaining the purpose, objectives, procedures, minimal risks and benefits of their participation in the research study. The researchers also issued a statement assuring the respondents that all data collected for the study will remain confidential and anonymous to ensure the participants’ safety and to protect their rights. If a respondent refuses to participate or wishes to terminate his involvement in the study, they were also allowed to do so. Before conducting interviews, the researchers provided a copy of the questionnaires to each respondent for their personal briefing and assessment of possible responses. The researchers also acquired informed consent from those in authority to perform data gathering at the LGUs at the two municipalities identified. The results of this study will also be presented with honesty and integrity, and proper acknowledgement and accreditation of all sources used will be given. 3.9 Bias One possible bias that the researchers might exercise in the study is the use of the National Disaster Risk Reduction and Management Framework as criteria for the effectiveness of the Disaster Risk Reduction and Management measures implemented by municipalities of Maria Aurora and Dipaculao in Aurora Province. The researchers, being Public Administration majors, did not look at the psychological and ethical effects of the efforts and initiatives of the LGUs disaster risk reduction and management and only focused on its effectiveness based on the criteria and the community knowledge management.

45

Due to the limitation of the study to only two municipalities, the study will not generally reflect the Local Disaster Risk Reduction and Management efforts of the whole province, but will only serve as a reflection and representative of the possible efforts conducted by local government units in coastal and land lock areas. 3.10 Limitations The study limits itself to the assessment and evaluation of the disaster risk reduction and management efforts of only two municipalities in the province of Aurora. Although the whole country is frequently affected by natural hazards especially by floods and landslides, the researchers have chosen the municipalities of Maria Aurora and Dipaculao to identify and assess the difference in the operationalization of the Disaster Risk Reduction and Management Act between a land lock and a coastal area. The results of the study are also limited by the honesty and non-biased participation of the participants. Another major limitation is the use of the National Disaster Risk Reduction and Management Framework as criteria for evaluating the effectiveness of the Local Government Unit in terms of implementing its local disaster risk reduction and management initiatives. This study will not reflect the perceived satisfaction of the stakeholders in terms of the implementation of the law; the perceived learning in the workshops conducted; and the perceived practical use of learning in meetings and workshops related to local disaster risk reduction and management. It will only reflect the relative compliance of the LGUs in the municipalities of Maria Aurora and Dipaculao to R.A. 10121.

46

CHAPTER IV RESULTS AND DISCUSSION

Community Knowledge Management (Questionnaire)

POPULATION PROFILE Table 2. Case Processing Summary Cases Valid N

Missing

Percent

N

Total

Percent

N

Percent

Age * Municipality

198

99.0%

2

1.0%

200

100.0%

Age * Barangay

198

99.0%

2

1.0%

200

100.0%

Education * Municipality

200

100.0%

0

.0%

200

100.0%

Education * Barangay

200

100.0%

0

.0%

200

100.0%

47

Table 3. Age - Municipality Cross tabulation

Municipality

Dipaculao Age

60 Total

Maria Aurora

Figure 5. Age Distribution per Municipalities Bar Chart

48

49

Table 4. Age – Barangay Cross tabulation

Barangay Salay Age

Total

Dinadiawan

Ipil

Diome

Sta. Lucia Cabituculan

Total

60

9

0

5

5

3

2

24

34

33

33

34

33

33

200

50

Figure 6. Age Distribution per Barangay Bar Chart

Table 5. Education – Municipality Cross tabulation

51

Municipality

Dipaculao Education

Total

Maria Aurora

Total

0

6

6

College

13

21

34

Elementary

13

21

34

High School

74

52

126

100

100

200

Figure 7. Education per Municipality Bar Chart

52

53

Table 5. Education - Barangay Cross tabulation

Barangay Salay Education

Dinadiawan

Ipil

Diome

Sta. Lucia

0

0

0

4

1

College

7

0

6

7

8

Elementary

8

0

5

5

8

19

33

22

18

16

34

33

33

34

33

High School Total

cont. Barangay Cabituculan Education

1

6

College

6

34

Elementary

8

34

18

126

33

200

High School Total

Total

Figure 8. Education per Barangay Bar Chart

54

FREQUENCY DISTIBUTION TABLE

Table 6. Respondents

Knowledge on the Knowledge topography on the overof land all house Educatio Municipali where the safety in case n ty Barangay house is built of disaster

Age N

Valid Missing

200

200

200

200

200

200

0

0

0

0

0

0

55

Knowledge on safety of Knowledge on the houses in Preparedness the safety of Preparedness their (Adequacy of appliances/ (Emergency community Preparedness emergency stocks) in case of furniture at (Emergency kits and disaster home kits) stocks) N

Valid Missing

200

200

200

200

200

0

0

0

0

0

Preparedness (Adequacy of emergency kits, stocks & Knowledge on the rescue equipment at presence of the the community evacuation/s helter site level)

N

Valid Missing

Knowledge Knowledge Knowledge on the on the safety on the safety location of of the of the the evacuation evacuation evacuation site (Physical site site structure) (Topography)

200

200

200

200

200

0

0

0

0

0

56

Knowledge Level of Knowledge on suitability Knowledge personal on LGU of LGU on the participation support in support in Knowledge adequacy of in DRRM case of case of LGU DRRM LGU DRRM programs of disasters disasters programs efforts the LGU N

Valid Missing

200

200

200

200

200

0

0

0

0

0

Knowledge on the importance Level of of community participation Community community participation efforts to in DRRM on DRRM LGU DRRM programs of issues programs the LGU N

Valid Missing

Materials used in the house

200

200

200

200

0

0

0

0

57

Table 7. Age

Frequency Percent Valid

60

24

12.0

12.1

100.0

Total

198

99.0

100.0

0

0

200

100.0

Missing System Total

Valid Percent

58

Table 8. Education

Frequency Percent Valid

Valid Percent

Cumulative Percent

6

3.0

3.0

3.0

College

34

17.0

17.0

20.0

Elementary

34

17.0

17.0

37.0

High School

126

63.0

63.0

100.0

Total

200

100.0

100.0

Table 9. Percentage per Municipality

Frequency Percent Valid Dipaculao

Valid Percent

Cumulative Percent

100

50.0

50.0

50.0

Maria Aurora

100

50.0

50.0

100.0

Total

200

100.0

100.0

59

Table 10. Percentage per Barangay

Frequency Percent Valid Salay

Valid Percent

Cumulative Percent

34

17.0

17.0

17.0

Dinadiawan

33

16.5

16.5

33.5

Ipil

33

16.5

16.5

50.0

Diome

34

17.0

17.0

67.0

Sta. Lucia

33

16.5

16.5

83.5

Cabituculan

33

16.5

16.5

100.0

200

100.0

100.0

Total

HOUSING

60

Table 11. Knowledge on the topography of land where the house is built

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

1

.5

.5

.5

Not Aware

10

5.0

5.0

5.5

Fairly Aware

68

34.0

34.0

39.5

Very Aware

121

60.5

60.5

100.0

Total

200

100.0

100.0

Table 12. Knowledge on the over-all house safety in case of disaster

Frequency Percent Valid Not Aware

Valid Percent

Cumulative Percent

13

6.5

6.5

6.5

Fairly Aware

78

39.0

39.0

45.5

Very Aware

109

54.5

54.5

100.0

Total

200

100.0

100.0

61

Table 13. Knowledge on the safety of appliances/furniture at home

Frequency Percent Valid Not Aware

Valid Percent

Cumulative Percent

12

6.0

6.0

6.0

Fairly Aware

110

55.0

55.0

61.0

Very Aware

78

39.0

39.0

100.0

Total

200

100.0

100.0

Table 14. Knowledge on safety of the houses in their community in case of disaster

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

2

1.0

1.0

1.0

27

13.5

13.5

14.5

Fairly Aware

142

71.0

71.0

85.5

Very Aware

29

14.5

14.5

100.0

Total

200

100.0

100.0

Not Aware

The Housing indicator includes four sets of questions regarding land topography, over-all house safety, and safety of community houses in case of disasters. The Table 11 shows that 60.5 percent of the respondents are ‘Very aware’, 34 percent are ‘Fairly aware’, and 10 percent are 62

‘Not aware’ about the topography of land where their house is built. Table 12 shows that more than half of the respondents are ‘Very aware’ (54 percent), less than half are ‘Fairly aware’ (39 percent), and only a number of respondents are ‘Not aware’ (6.5 percent) of their over-all house safety. On the other hand, Table 13 shows medium community knowledge on the safety of appliances or furniture in their own houses, with 55 percent of the respondents answering ‘Fairly aware’, 39 percent ‘Very Aware’, and only 6 percent ‘Not aware’. Table 14 describes knowledge of the respondents on community house safety. As shown in the table, 71 percent of the respondents are ‘Fairly aware’ about their community house safety, 14.5 percent are ‘Very aware’, and 13.5 percent are ‘Not aware’.

STORAGE Table 15. Preparedness (Emergency kits)

Frequency Percent Valid Not prepared

Valid Percent

Cumulative Percent

37

18.5

18.5

18.5

Fairly prepared

78

39.0

39.0

57.5

Very prepared

85

42.5

42.5

100.0

200

100.0

100.0

Total

63

Table 16. Preparedness (Emergency stocks)

Frequency Percent Valid Not prepared

Valid Percent

Cumulative Percent

38

19.0

19.0

19.0

Fairly prepared

78

39.0

39.0

58.0

Very prepared

84

42.0

42.0

100.0

200

100.0

100.0

Total

Table 17. Preparedness (Adequacy of emergency kits and stocks)

Frequency Percent Valid Not prepared Fairly prepared Very prepared Total

Valid Percent

Cumulative Percent

34

17.0

17.0

17.0

123

61.5

61.5

78.5

43

21.5

21.5

100.0

200

100.0

100.0

64

Table 18. Preparedness (Adequacy of emergency kits, stocks & rescue equipment at the community level)

Frequency Percent Valid Not prepared Fairly prepared Very prepared Total

Valid Percent

Cumulative Percent

36

18.0

18.0

18.0

131

65.5

65.5

83.5

33

16.5

16.5

100.0

200

100.0

100.0

The Storage indicator includes preparedness and adequacy indices covering personal and community emergency kits, emergency stocks, rescue and emergency population equipment. The table 15 shows a very prepared and fairly prepared population in terms of personal preparation of emergency kits, with 85 and 75 percent comprising each index, respectively. Only 18.5 percent are not prepared or do not have emergency kits in their own houses. Corollary to the preceding table, Table 16 also shows a very and fairly prepared respondent population in terms of personal and household emergency stocks. Only 19 percent admitted not being prepared in terms of stocking emergency goods for disasters. Despite having more respondents who rated themselves ‘Very prepared’ in the preceding indices, more respondents admitted being fairly prepared in terms of adequacy of emergency kits and stocks. As shown in table 17, only 21 percent rated ‘Very prepared’, and 17 percent admitted not having adequate emergency kits and stocks in their own houses. This is also true in table 18 that describes Community preparedness in terms of adequacy of emergency kits, stocks and emergency equipment. Only 16.5 percent rated the community being ‘Very prepared’, 65.5 rated ‘Fairly prepared’, and 18 percent rated ‘Not prepared’. 65

SHELTER/EVACUATION SITE Table 19. Knowledge on the presence of the evacuation/shelter site

Frequency Percent Valid Not Aware

Valid Percent

Cumulative Percent

48

24.0

24.0

24.0

Fairly Aware

29

14.5

14.5

38.5

Very Aware

123

61.5

61.5

100.0

Total

200

100.0

100.0

Table 20. Knowledge on the location of the evacuation site

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

1

.5

.5

.5

Not Aware

45

22.5

22.5

23.0

Fairly Aware

20

10.0

10.0

33.0

Very Aware

134

67.0

67.0

100.0

Total

200

100.0

100.0

66

Table 21. Knowledge on the safety of the evacuation site (Physical structure)

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

1

.5

.5

.5

Not Aware

44

22.0

22.0

22.5

Fairly Aware

62

31.0

31.0

53.5

Very Aware

93

46.5

46.5

100.0

200

100.0

100.0

Total

Table 22. Knowledge on the safety of the evacuation site (Topography)

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

5

2.5

2.5

2.5

Not Aware

44

22.0

22.0

24.5

Fairly Aware

58

29.0

29.0

53.5

Very Aware

93

46.5

46.5

100.0

200

100.0

100.0

Total

The Shelter and Evacuation indicator covers personal knowledge on the presence, location, and safety in terms of physical structure and topography of the evacuation site. All tables show high awareness in all identified indices yet a higher percentage in low awareness is also reflected. As shown in table 19, 61.5 percent of the respondents admitted being very aware 67

of having an evacuation within the barangay or municipality, 14.5 percent are ‘Fairly aware’, and 24 percent of the respondents are not aware of its existence. The same trend can also be observed in table 20 that describes respondent knowledge on the location of the evacuation site. 67 percent of the 200 respondents are ‘Very aware’, only 10 percent are ‘Fairly aware’, and 22.5 percent are ‘Not aware’ of the evacuation site location. On the other hand, both tables regarding evacuation site safety ( and ) reflect a more varied respondent knowledge in terms of the physical structure and topography of the evacuation site. In table 21, 46 percent admitted having high awareness, 32 percent have fair awareness, and 22 percent have low awareness. Table 22 shows 46 percent of the respondents having high awareness, 29 percent fair awareness, and only 22 percent have low awareness.

LGU SUPPORT Table 23. Knowledge on LGU support in case of disasters

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

1

.5

.5

.5

Not Aware

71

35.5

35.5

36.0

Fairly Aware

91

45.5

45.5

81.5

Very Aware

37

18.5

18.5

100.0

200

100.0

100.0

Total

68

Table 24. Knowledge on suitability of LGU support in case of disasters

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

1

.5

.5

.5

71

35.5

35.5

36.0

Fairly Appropriate

102

51.0

51.0

87.0

Very Appropriate

26

13.0

13.0

100.0

200

100.0

100.0

Not Appropriate

Total

Table 25. Knowledge LGU DRRM programs

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

1

.5

.5

.5

Not Aware

81

40.5

40.5

41.0

Fairly Aware

85

42.5

42.5

83.5

Very Aware

33

16.5

16.5

100.0

Total

200

100.0

100.0

69

Table 26. Knowledge on the adequacy of LGU DRRM efforts

Frequency Percent Valid NA Not adequate Fairly adequate Very adequate Total

Valid Percent

Cumulative Percent

1

.5

.5

.5

79

39.5

39.5

40.0

101

50.5

50.5

90.5

19

9.5

9.5

100.0

200

100.0

100.0

Local Government Support covers knowledge of LGU support in case of disasters, LGU Disaster Risk and Reduction Management Programs, adequacy of LGU DRRM efforts, and personal participation in LGU DRRM efforts. Table 23 shows that surprisingly, more respondents are Fairly and Not aware of LGU support during disasters. Only 18.5 percent of the population is Very aware. This data is also validated in Table 24 which shows a higher percentage in respondents who rated ‘Fairly Appropriate’ (51%) and ‘Not Appropriate’ (35.5%). Only 13 percent of the respondents rated ‘Very Appropriate’ LGU support in case of disasters. Moreover, respondent knowledge on LGU DRRM programs reflects little difference between raters of ‘Not aware’ and ‘Fairly aware’. As shown in table 25, 42.5 percent rated Fairly aware, 40.5 percent rated Not Aware, and only 16 percent rated high awareness in LGU DRRM programs. This trend is further reflected in Table 26 where only 50.5 percent rated being ‘Fairly aware’ of the adequacy of LGU DRRM efforts, 39.5 percent rated being ‘Not aware’, and only 9.5 percent rated ‘Very Aware’.

COMMUNITY LINKAGE 70

Table 27. Level of personal participation in DRRM programs of the LGU

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

1

.5

.5

.5

Not Active

44

22.0

22.0

22.5

Fairly Active

83

41.5

41.5

64.0

Very Active

72

36.0

36.0

100.0

Total

200

100.0

100.0

Table 28. Level of community participation in DRRM programs of the LGU

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

2

1.0

1.0

1.0

Not Active

44

22.0

22.0

23.0

Fairly Active

95

47.5

47.5

70.5

Very Active

59

29.5

29.5

100.0

Total

200

100.0

100.0

71

Table 29. Community participation on DRRM issues

Frequency Percent Valid NA Not Active Fairly Active Very Active Total

Valid Percent

Cumulative Percent

1

.5

.5

.5

49

24.5

24.5

25.0

110

55.0

55.0

80.0

40

20.0

20.0

100.0

200

100.0

100.0

Table 30. Knowledge on the importance of community efforts to LGU DRRM programs

Frequency Percent Valid NA

Valid Percent

Cumulative Percent

3

1.5

1.5

1.5

2

1.0

1.0

2.5

Fairly Active

41

20.5

20.5

23.0

Very Active

154

77.0

77.0

100.0

Total

200

100.0

100.0

Not Active

The Community linkage indicator includes four sets of questions regarding level of personal and community participation in LGU DRRM programs and issues, and importance of community efforts to LGU programs. The table 27 shows that 36 percent of the respondents are 72

‘Very active’, 41.5 percent are ‘Fairly active’, and 22 percent are ‘Not active’ in the DRRM programs of the LGU. In terms of community participation in DRRM programs of the LGY, table 28 shows that 29.5 percent of the respondents think that the community is ‘Very active’, 47.5 percent rated ‘Fairly active’, and 22 percent thinks the community is ‘Not active’. On the other hand, table 29 shows medium community involvement in DRRM issues, with 55 percent of the respondents answering ‘Fairly active’, 20 percent ‘Very Active’, and 24.5 percent being ‘Not aware’. Table 30 describes knowledge of the respondents on community efforts to LGU programs. As shown in the table, 77 percent of the respondents are ‘Fairly aware’ about their community house safety, 20.5 percent are ‘Very aware’, and only one percent of the respondents are ‘Not aware’.

Table 31. Materials used in the house

Frequency Percent Valid

Valid Percent

Cumulative Percent

8

4.0

4.0

4.0

Heavy

104

52.0

52.0

56.0

Iba pa

2

1.0

1.0

57.0

Light

48

24.0

24.0

81.0

Light and Heavy

38

19.0

19.0

100.0

200

100.0

100.0

Total

ANALYSIS OF VARIANCE 73

Hypothesis Testing F-TEST As stated in the section 3.5 (Population and Sampling) of Methodology, this study focused on two populations (2 municipalities) and within each municipalities are six barangays. The total sample size for both populations is 200 respondents. The researchers used the Confidence Interval 1-.95 = .05, and computed the intersection between degrees of freedom (Fstatistic) to be 2.21.

HOUSING

74

Table 32. Descriptives

Knowledge on the topography of land where the house is built

Knowledge on the over-all house safety in case of disaster

Knowledge on the safety of appliances/furniture at home

Knowledge on safety of the houses in their community in case of disaster

N

Mean

Std. Deviation

Dipaculao

100

8.12

2.675

.268

Maria Aurora

100

7.48

3.037

.304

Total

200

7.80

2.873

.203

Dipaculao

100

7.68

3.031

.303

Maria Aurora

100

7.25

2.840

.284

Total

200

7.47

2.938

.208

Dipaculao

100

6.76

2.818

.282

Maria Aurora

100

6.66

2.790

.279

Total

200

6.71

2.797

.198

Dipaculao

100

5.79

2.575

.258

Maria Aurora

100

4.48

2.158

.216

Total

200

5.14

2.459

.174

Std. Error

Table 32 shows that the population means for the variable Knowledge on the topography of land where the house is built is 7.48 for Maria Aurora and 8.12 for Dipaculao. In the variable Knowledge on the over-all house safety in case of disaster, Maria Aurora scored 7.25 and 7.68 for Dipaculao. Knowledge on the safety of appliances/furniture at home shows population means of 6.66 for Maira Aurora and 6.76 for Dipaculao, and Knowledge on 75

safety of the houses in their community in case of disaster shows population means of 4.48 for Maria Aurora and 5.79 for Dipaculao.

Table 33. Analysis of Variance (ANOVA)

Sum of Squares Knowledge on the topography of land where the house is built

Knowledge on the over-all house safety in case of disaster

Knowledge on the safety of appliances/furniture at home

Knowledge on safety of the houses in their community in case of disaster

Degrees of Freedom (df) Mean Square

Between Groups

20.480

1

20.480

Within Groups

1621.520

198

8.189

Total

1642.000

199

Between Groups

9.245

1

9.245

Within Groups

1708.510

198

8.629

Total

1717.755

199

Between Groups

.500

1

.500

Within Groups

1556.680

198

7.862

Total

1557.180

199

Between Groups

85.805

1

85.805

Within Groups

1117.550

198

5.644

Total

1203.355

199

76

Knowledge on the topography of land where the house is built

Between Groups

F

Sig.

2.501

.115

1.071

.302

.064

.801

15.202

.000

Within Groups Total

Knowledge on the over-all house safety in case of disaster

Between Groups Within Groups Total

Knowledge on the safety of appliances/furniture at home

Between Groups Within Groups Total

Knowledge on safety of the houses in their community in case of disaster

Between Groups Within Groups Total

Hypotheses testing and F-Statistic: •

Knowledge on the topography of land where the house is built 2.501>2.21 = Reject Null Ha: One or more citizens differ in the level of knowledge on the topography of land where the house is built.

77

•

Knowledge on the over-all house safety in case of disaster 1.071