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    Mitigating impacts of disaster through community resilience : whakawhanaungatanga vs. zombies : an exegesis presented in partial fulfilment of the requirements for the degree of Masters of Design at Massey University, Wellington, New Zealand
    (Massey University, 2025) Koedijk, Paige
    This research contributes to the field of disaster risk reduction by utilising visual storytelling to emphasise the critical role of resilient communities in mitigating the impacts of climate-accelerated disasters, which disproportionately affect vulnerable populations. The Peninsula, a fictional pānui, explores the mātauranga Māori principle of whakawhanaungatanga through the depiction of ordinary members from the Miramar Peninsula community in tongue-in-cheek survival situations during an ongoing zombie catastrophe. Leveraging Wellingtonians’ appreciation for b-horror/humour storytelling seen in productions such as What We Do in the Shadows and Wellington Paranormal, the use of humour and the spectacle of a zombie context is an engaging narrative experience for readers to consider their contributions within their community in an emergency. Some social change campaigns have gained viral levels of success through the use of evocative visuals and narratives to resonate with the public, as seen in Aotearoa’s COVID-19 infographics and the CDC’s 2011 zombie-themed hurricane information. The zombie as a narrative device functions as a versatile symbol for political or socio-economic commentary, serving in this research as a “trojan-horse” for conveying emergency management information with a community focus. The social collaboration illustrated in The Peninsula mirrors the real world advantage of community resilience throughout the phases of an emergency. The design output is explored through affective design and developed through iterative cycles of “inquiry by design” methodologies and implementing community-based social marketing strategies.
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    Mobilizing citizens for reducing disaster risks : a study of communication practices aimed at encouraging civic participation and collective action in disaster preparedness in Aotearoa New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand
    (Massey University, 2024-12-30) Das, Manomita
    Community-based disaster risk reduction (DRR) approaches provide an effective means of reducing the impacts of extreme events caused by natural hazards. Such approaches involve engaging with ‘at-risk’ communities in the pre-disaster stage and supporting them to reduce their risks through preparedness actions. These preparedness actions operate both at an individual level such as having emergency kits and personal preparedness items and at a community level such as developing community response plans and establishing community response groups through collective community actions. While individual preparedness actions are well-documented in New Zealand (NZ), there is limited research examining collective actions in DRR and their facilitators. This is a critical gap as many disaster risks cannot be substantially reduced by individual efforts alone and require collective community wide efforts. Moreover, central to involving community in DRR is communication. While a strong knowledge base on communication for individual preparedness actions exist, there is a lack of clarity on how communication can promote people’s participation and collective actions in DRR. This research, therefore, aims to achieve two key objectives: first, to understand collective actions in DRR in NZ, exploring their forms, enablers, barriers, and outcomes; and second, to examine how communication can be leveraged to support and enhance these collective actions. An exploratory sequential mixed methods approach was adopted. For qualitative data, a multi-case study was conducted. The findings were derived through thematic and cross-case analysis of 35 interviews with emergency management officials and community members, observation notes of community events and field visits and review of communication materials and documents. Quantitative data included 80 survey responses from volunteers and community members participating in collective actions for DRR. The findings provide important insights on collective community actions in DRR and the role of communication in supporting them. Firstly, the study outlines three forms of people’s participation in DRR: volunteering with New Zealand Response Teams, participation in local community emergency response teams, and involvement through existing community groups like resident associations or sports clubs. Key factors triggering participation include heightened hazard awareness and initiation by emergency management agencies. Trusted local facilitators, community dialogue, and institutional support sustain collective actions, while challenges like low community interest and bureaucratic barriers hinder them. The findings highlight that civic participation in DRR in New Zealand is response-centric and lacks a proactive approach towards preventing risk creation and mitigating local hazards. Secondly, using a communication ecology perspective and drawing on the Communication Infrastructure Theory, the research explores the communication processes, actors, and resources that foster or hinder collective participation in DRR. The data reveals that civil defence emergency management agencies, different government organizations, non-governmental and community-based agencies, and local people serve as key communicating actors. Community centres, schools, and public libraries are critical resources within the community communication network serving as hubs for community involvement where residents participate in emergency management activities, engage in dialogue, and collaborate to address disaster risks. Relationship building activities, awareness events, advertisements and community conversations play an important role in the communication process. Contextual factors such as safety and accessibility of the social infrastructure, presence of skilled facilitators, existing community organizations with networks and relationships and supporting institutional and resourcing mechanisms also influence civic participation and collective action in DRR. Thirdly, the research finds that communication approaches to promote civic participation in DRR heavily rely on two-way conversations between emergency managers, community members and other stakeholders. These conversations flow through narratives conveying disaster risks and preparedness messages, rather than factual argumentation. Four key themes were identified in the narratives - connection and care (encouraging people to care for their communities and build support networks), everyday heroes (highlighting the value of simple actions in emergencies), collective efficacy (emphasizing the ability of community members to work together toward DRR goals), and collective responsibility (underscoring the shared duty to address local risks). While the narratives are generally helpful in promoting community agency and fostering social capital, some narratives, particularly the collective responsibility narrative, was found to be problematic which creates confusion and frustration. Lastly, the findings highlight the growing role of social media in supporting collective DRR actions at the community level. They demonstrate how social media helps in maintaining conversations on preparedness in regular discourse and serves as a communication platform for communities of practice in preparedness. Neighbourhood based social media pages are valuable to promote civic participation in DRR and are most widely used compared to other Web 2.0 based applications. The thesis makes an important contribution to the academic and practical understanding of collective actions in DRR and the role of communication in facilitating them. It provides an overview of forms and facilitators of collective actions in NZ, addressing a gap in existing literature. Additionally, the findings advance communication research on disaster and community resilience by adopting the relational network perspective which is an emerging area of research. The findings offer an evidence base for policy and programme development, particularly for advancing NZ’s National Disaster Resilience Strategy (2019). By advancing the existing knowledge base, this thesis is expected to support meaningful civic participation and collective action, empowering communities to reduce disaster risks and improve their resilience.
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    Prioritising indicators of success in 'Build Back Better' post-disaster frameworks : a thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Construction at Massey University, Albany, New Zealand
    (Massey University, 2025-07-30) Hubbard, Francis
    This study explores the challenges and significance of indicator selection for key decision-makers in post-disaster response, recovery, and reconstruction efforts. When a community is overwhelmed in the aftermath of a disaster - various entities, including aid organisations, local authorities, and national agencies, are mobilised to provide emergency response and support in the subsequent response and recovery phases. These decision-makers rely on choosing appropriate indicators to evaluate the effectiveness of their interventions, track progress, and decide on appropriate actions and activities. Guided by the principle of "Build Back Better," which advocates for a comprehensive and holistic approach to resilience, practitioners need to comprehend the intricate relationships and dependencies among indicators to make informed decisions regarding their selection. This aspect has been identified as a significant weakness in the implementation process for all stakeholders. Employing a novel methodology, this thesis utilises the Hierarchical Decomposition Algorithm to analyse the priority of and the relationship between indicators proposed by the 2016 ‘Build Back Better Framework’, a synthesised framework reflecting a unified approach in disaster management. Empirical evidence from forty case studies examining key decision makers experiences of implementing disaster response efforts validates these findings. The study concludes with a rational process and workflow for determining indicator selection which considers the diverse nature of response and recovery in the pursuit to effectively build back better.
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    Development of a community-engaged, low-cost earthquake early warning system using MEMS-based sensors : enhancing and adapting the PLUM algorithm with decentralised processing and P-wave integration : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand
    (Massey University, 2025-03-04) Chandrakumar, Chanthujan
    Earthquakes pose a significant threat to people and infrastructure, particularly in regions near active faults or offshore subduction zones, which are more frequently exposed to moderate to strong shaking. Earthquake Early Warning Systems (EEWS) provide crucial alerts immediately following an earthquake, offering a warning window ranging from a few seconds to tens of seconds. These systems have effectively reduced damage and allowed individuals to take protective actions. However, the high cost of establishing high-end EEWSs makes them unaffordable for many countries. To address this, there is growing interest in using low-cost technologies such as Micro-Electromechanical Systems (MEMS)-based ground motion sensors to implement EEWSs. However, despite their potential, several knowledge gaps must be addressed to enhance their efficiency and effectiveness. Firstly, further investigation into decentralised processing for earthquake detection and alert generation is required. Traditional high-end EEWSs often rely on centralised processing units, which have proven vulnerable to critical delays and communication failures during major seismic events. Secondly, adapting and improving ground-motion-based or wave-field-based EEW algorithms is crucial for enhancing their performance, ensuring that EEWSs can provide timely and effective warnings in all regions during an earthquake, as opposed to the limitations posed by traditional source-based methods. This doctoral research addresses these gaps by developing and evaluating a community-engaged, low-cost MEMS-based EEWS. The system utilises a ground-motion-based EEW algorithm adapted for decentralised processing, enabling rapid earthquake detection. It also integrates a P-wave detection algorithm to enhance the performance of the ground-motion-based approach. Guided by the Design Science Research methodology, this study seeks to answer three key research questions: (1) How can the Propagation of Local Undamped Motion (PLUM) ground-motion-based EEW algorithm be adapted and implemented for New Zealand’s seismic conditions using decentralised processing? (2) How can high-accuracy P-wave detection be achieved in a community-engaged EEW network with high ambient noise? (3) How can the P-wave detection algorithm be integrated into the adapted PLUM algorithm to extend the warning window? The study begins with a comprehensive literature review to identify research gaps in low-cost MEMS-based EEWSs, leading to the formulation of the research questions addressed in this thesis. To answer these questions, an experimental community-engaged EEW network was implemented in Greater Wellington, NZ, using low-cost MEMS-based sensors. This implementation was followed by adapting the PLUM algorithm to NZ-PLUM, making it compatible with New Zealand’s seismic intensity by employing region-specific Ground Motion Intensity Conversion Equations. The NZ-PLUM algorithm was then integrated into a sensor network operating under a decentralised processing architecture using a two-tier communication model, ensuring rapid and reliable data transmission and processing. Building upon the implementation of the NZ-PLUM algorithm, integrating a P-wave detection algorithm into the NZ-PLUM approach was explored to extend the warning window. A performance analysis is conducted to identify the most effective P-wave detection algorithm for integration into the community-engaged EEWS. Subsequently, an empirical relationship between P-wave and S-wave amplitudes is established, leading to the development of a P-wave-based PLUM algorithm (NZ-PLUM-P), which provides an extended warning window before the onset of seismic shaking. The outcomes of this doctoral research make significant advancements in community-engaged, low-cost EEWSs. A key contribution is developing a real-life experimental EEW network using two distinct algorithms, NZ-PLUM and NZ-PLUM-P, tailored to NZ’s seismic context within a decentralised processing architecture. This study offers a versatile framework applicable to implementing community-engaged EEW networks at a low cost, making a substantial contribution to theory and practice. The methods developed for P-wave detection, constructing P-S wave amplitude relationships, executing EEW algorithms using decentralised processing and evaluating EEW network performance provide valuable tools for future research and implementation. Further, this cost-effective, community-driven model not only offers a viable solution for seismically active nations with limited resources but also has the potential to enhance the performance of existing high-end EEWS by increasing sensor density and extending warning capabilities. Providing earthquake early warnings can potentially be crucial in saving lives, protecting critical infrastructure, and enhancing public preparedness.
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    Animal responders : risks and mitigation strategies : a thesis presented in fulfilment of the requirements for the degree of Master of Veterinary Science at Massey University, Manawatu, New Zealand
    (Massey University, 2023) De Grey, Steven John
    Although disasters are often defined by their effect on the human populace, animals are not spared and are likewise affected. As animal and human welfare are interconnected, in disasters both will be affected and an assault on one will impact the other. Disasters are expected to become more frequent so in order to manage human safety and welfare, we must manage animal safety and welfare. The safest way to respond to animals in emergencies is to use emergency responders trained in animal behaviour and rescue techniques, however there is a lack of knowledge in this domain. This study aims to identify the factors that impact an emergency responder’s health during and after an animal rescue or disaster response and to identify mitigation techniques that can be utilised to enhance their safety and resilience. An anonymous online survey was used to enquire about the responder, the impact of a recent animal-related event and the effectiveness of a selection of mitigation strategies. This study found that a significant proportion of respondents had experienced physical injuries to the arms and hands, with the animal and fatigue being common causative factors. Another finding was that there is a risk of a psychological injury and a diagnosis of post-traumatic stress disorder was likely for some respondents. Despite these risks, the majority of respondents reported that they found the animal rescue event a positive experience. Psychosocial support was found to be an effective recovery technique along with physical or recreational activity, debriefing, and mindfulness. Other mitigation options for both responders and organisations were identified from the literature such as psychological and crew resource management training and the use of the ‘buddy system’. In conclusion, this study adds to the limited literature in this realm and will make a significant contribution to the safety and resilience of trained animal responders.
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    Infrastructure planning emergency levels of service for the Wellington region, Aotearoa New Zealand : a thesis presented in fulfilment of the requirements for the degree of Doctor of Philosophy in Psychology (Emergency Management) at Massey University, Wellington, New Zealand
    (Massey University, 2024-06-07) Mowll, Richard
    Past work has demonstrated that the infrastructure in the Wellington region, Aotearoa New Zealand, is vulnerable to natural hazard events such as earthquake and tsunami. To enable common understandings of the levels of service (or targets) that critical infrastructure entities are planning on delivering in an emergency event, the concept of ‘planning emergency levels of service’ (PELOS) is developed and presented in this thesis. Such a concept is readily relatable to the water sector where, for example, the World Health Organisation’s ‘basic access’ to water standard is for ’20 litres of water, per person, per day, within 1km of the dwelling’. Despite such standards for water, there are few other examples in the sectors of energy, telecommunications and transport. A literature review investigated relevant sources of information on the concept from both academic and from infrastructure sector-specific texts and was used in developing a preliminary framework of PELOS, alongside discussions with emergency management experts in the Wellington region. The overall PELOS concept and preliminary framework was then presented in interviews and workshops with key stakeholders, and qualitative data collected from these interactions was used to create an ‘operationalised’ PELOS framework. This framework was adopted by the Wellington Lifelines Group, a grouping of the critical infrastructure entities in the region. Key themes of the PELOS concept are explored, namely: interdependencies, the need to consider the vulnerabilities of some community members, emergency planning considerations, stakeholders’ willingness to collaborate and the flexibility/adaptability of the delivery of infrastructure services following a major event. Further, a description of the process taken to develop the framework is provided to enable other regions to create their own frameworks. A mapping tool, visualising where PELOS can, and cannot, be achieved based on hazard impact modelling is presented. This allows the infrastructure entities, the impacted communities and the emergency management sector to have a common understanding of the targets of response following a major hazard event, and plan for them in future.
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    Understanding how to communicate multi-hazard and cascading hazard and risk information to aid disaster risk planning : a thesis presented in partial fulfilment of the requirement for the degree of Masters in Emergency Management at Massey University, Wellington, New Zealand
    (Massey University, 2023) Lascarides, Sophie
    Driven by climate change, population growth, land use intensification, and an ever more interconnected world, disaster events are becoming more frequent, more severe, more costly, and more complex. As such, multi-hazard risk reduction, including robust data collection and decision-making, is increasingly important to ensure that the inevitable emergencies we respond to are less disastrous. Nine professionals drawn from the Aotearoa New Zealand hazard and disaster ‘risk reduction sector’ (including technical specialists, emergency management professionals, and local and central government staff) were interviewed via semi-structured interviews to discuss their understanding and use of multi-hazard and cascading hazard and risk information for disaster risk reduction purposes. Professional context was found to be strongly influenced by the specificities of New Zealand legislation and the relationship between legislative requirements (including but not limited to the Resource Management Act 1991, Civil Defence Emergency Management Act 2002, Building Act 2004 and Local Government Act 2002). These professionals use overlapping terms such as ‘multi-hazard’, ‘cascading hazard’ and ‘compounding hazard’, sometimes interchangeably, to describe a range of concepts, including the increasingly common situation where shocks or failures in one part of a system spill across to others. This complex interaction of potential risk, events, impacts and their conceptualisation presents a challenge for effective communication with and between decision-makers, the public, and peer organisations regarding disaster risk reduction. Consequently, consideration needs to be given to how to communicate such concepts so that they can be understood and used effectively in decision-making. The interview findings suggest that narrative communication might be a possible solution. The merits of using narrative communication, in the context of risk communication, are discussed within this thesis. Narrative is recognised as a method of organising, understanding and communicating complex information, and is found to have potential as a frame for communicating multi and cascading hazard and risk information. Additionally, guiding principles are proposed based on the results of the interviews to assist the development of more effective hazard model outputs and supporting communication products, recognising the power of a good story, well-designed graphics, and audience-appropriate scaffolding.
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    D2D communication based disaster response system under 5G networks : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy (PhD) in Computer and Electronics Engineering, Massey University, Auckland, New Zealand
    (Massey University, 2023-12-14) Ahmed, Shakil
    Many recent natural disasters such as tsunamis, hurricanes, volcanoes, earthquakes, etc. have led to the loss of billions of dollars, resources and human lives. These catastrophic disasters have attracted the researchers’ attention onto the significant damage to communication infrastructure. Further, communication within the first 72 hours after a disaster is critical to get help from rescuers. The advancement of wireless communication technologies, especially mobile devices and technologies, could help improve emergency communication systems. The next generation of mobile networks and technologies such as Device to Device (D2D) communication, the Internet of Things (IoT), Blockchain, and Big Data, can play significant roles in overcoming the drawbacks of the current disaster management system for data analysis and decision making. Next-generation cellular 5G and 6G network will provide several complex services for mobile phones and other communication devices. To integrate those services, the 5G cellular network will have the capabilities to handle the significant volume of data rate and the capacity to handle traffic congestion compared with the 4G or 3G cellular network. D2D communication technology, one of the major technologies in the 5G network, has the capability to exchange a high volume of traffic data directly between User Equipment (UE) without additional control from the Base Station(BS). D2D communication is used with other cell tiers in the 5G heterogeneous network (HetNet). Thus, the devices can form a cluster and cooperate with each other. As a result, the system tremendously increases network capacity as devices inside the cluster reuse the same spectrum or use an unlicensed spectrum. It will help to reduce the network’s traffic load and achieve significant throughput. D2D communication also has the ability to increase area spectral efficiency, reduce device power consumption, outage probabilities and improve network coverage. All of these characteristics are vital parameters for public safety and emergency communication applications. IoT paradigm is another promising technology with exciting features such as heterogeneity, interoperability, and flexibility. IoT has the capability to handle vast amounts of data. This huge amount of data creates Data security and data storage problems. Though, there are many technologies used to overcome the problem of validating data authenticity and data storage. Out of them, the Blockchain system is one of the emerging technologies which provides intrinsic data security. In addition, Big data technology provides data storage, modification, process, visualisation and representation in an efficient and easily understandable format. This feature is essential for disaster applications because it requires quickly collecting and processing vast amounts of data for a prompt response. Therefore, the main focus of this research work is exploring and utilising these emerging technologies (D2D, IoT, Big Data and Blockchain) and validating them with mathematical modelling for developing a disaster response system. This thesis proposes a disaster response framework by integrating the emerging technologies to overcome the problem of data communication, data security, data analysis and visualisation. Mathematical analysis and simulation models for multiple disaster sizes were developed based on D2D communication system. The result shows significant improvement in the disaster framework performance. The Quality of Services (QoS) is calculated for different scales of disaster impact. Approximately 40% disaster-affected people can get 5-10 dB and approximately 20% users get 20-25 dB Signal to Interference and Noise Ratio (SINR) when 70% infrastructure is damaged by a disaster. The network coverage increased by 25% and the network lifetime increased by 8%-14%. The research helps to develop a resilient disaster communication network which minimises the communication gap between the disaster-affected people and the rescue team. It identified the areas according to the needs of the disaster-affected people and offered a viable solution for the government and other stakeholders to visualize the disaster’s effect. This helps to make quick decisions and responses for pre and post-disaster.
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    Multi-source multimodal deep learning to improve situation awareness : an application of emergency traffic management : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand
    (Massey University, 2023) Hewa Algiriyage, Rangika Nilani
    Traditionally, disaster management has placed a great emphasis on institutional warning systems, and people have been treated as victims rather than active participants. However, with the evolution of communication technology, today, the general public significantly contributes towards performing disaster management tasks challenging traditional hierarchies in information distribution and acquisition. With mobile phones and Social Media (SM) platforms widely being used, people in disaster scenes act as non-technical sensors that provide contextual information in multiple modalities (e.g., text, image, audio and video) through these content-sharing applications. Research has shown that the general public has extensively used SM applications to report injuries or deaths, damage to infrastructure and utilities, caution, evacuation needs and missing or trapped people during disasters. Disaster responders significantly depend on data for their Situation Awareness (SA) or the dynamic understanding of “the big picture” in space and time for decision-making. However, despite the benefits, processing SM data for disaster response brings multiple challenges. Among them, the most significant challenge is that SM data contain rumours, fake information and false information. Thus, responding agencies have concerns regarding utilising SM for disaster response. Therefore, a high volume of important, real-time data that is very useful for disaster responders’ SA gets wasted. In addition to SM, many other data sources produce information during disasters, including CCTV monitoring, emergency call centres, and online news. The data from these sources come in multiple modalities such as text, images, video, audio and meta-data. To date, researchers have investigated how such data can be automatically processed for disaster response using machine learning and deep learning approaches using a single source/ single modality of data, and only a few have investigated the use of multiple sources and modalities. Furthermore, there is currently no real-time system designed and tested for real-world scenarios to improve responder SA while cross-validating and exploiting SM data. This doctoral project, written within a “PhD-thesis-withpublication” format, addresses this gap by investigating the use of SM data for disaster response while improving reliability through validating data from multiple sources in real-time. This doctoral research was guided by Design Science Research (DSR), which studies the creation of artefacts to solve practical problems of general interest. An artefact: a software prototype that integrates multisource multimodal data for disaster response was developed adopting a 5-stage design science method framework proposed by Johannesson et al. [175] as the roadmap for designing, developing and evaluating. First, the initial research problem was clearly stated, positioned, and root causes were identified. During this stage, the problem area was narrowed down to Emergency traffic management instead of all disaster types. This was done considering the real-time nature and data availability for the artefact’s design, development and evaluation. Second, the requirements for developing the software artefacts were captured using the interviewing technique. Interviews were conducted with stakeholders from a number of disaster and emergency management and transport and traffic agencies in New Zealand. Moreover, domain knowledge and experimental information were captured by analysing academic literature. Third, the artefact was designed and developed. The fourth and final step was focused on the demonstration and evaluation of the artefact. The outcomes of this doctoral research underpin the potential for using validated SM data to enhance the responder’s SA. Furthermore, the research explored appropriate ways to fuse text, visual and voice data in real-time, to provide a comprehensive picture for disaster responders. The achievement of data integration was made through multiple components. First, methodologies and algorithms were developed to estimate traffic flow from CCTV images and CCTV footage by counting vehicle objects. These outcomes extend the previous work by annotating a large New Zealand-based vehicle dataset for object detection and developing an algorithm for vehicle counting by vehicle class and movement direction. Second, a novel deep learning architecture is proposed for making short-term traffic flow predictions using weather data. Previous research has mostly used only traffic data for traffic flow prediction. This research goes beyond previous work by including the correlation between traffic flow and weather conditions. Third, an event extraction system is proposed to extract event templates from online news and SM text data, answering What (semantic), Where (spatial) and When (temporal) questions. Therefore, this doctoral project provides several contributions to the body of knowledge for deep learning and disaster research. In addition, an important practical outcome of this research is an extensible event extraction system for any disaster capable of generating event templates by integrating text and visual formats from online news and SM data that could assist disaster responders’ SA.
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    Disaster risk reduction considerations for big bodied people in Aotearoa New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, Aotearoa New Zealand
    (Massey University, 2022) Gray, Lesley
    Big bodied people have been left behind in disasters and are conspicuously absent in disaster risk reduction planning, policies and practices. This exploratory study addresses the needs and considerations of big bodied people relating to disaster risk reduction. Aotearoa New Zealand is well suited as the setting for this study with the experience of a wide range of natural hazards and recent, significant disasters, and importantly in relation to body size demographics, having very high population levels of body mass. There is a dearth of research on this topic. Descriptive qualitative methodology was applied, framed by a pragmatic worldview in order to build knowledge from the perspectives and experiences of 55 emergency managers and 17 people identifying as big bodied. These were explored through an online survey and semi-structured interviews. Descriptive and reflexive thematic analysis of the data were undertaken. The research findings, presented in three publications, highlight the complexities of disaster risk reduction for big bodied people and emergency managers. A number of assumptions and expectations were identified that may explain why there has been scant, if any, consideration of the needs of BBP in a disaster particular to size, shape and weight. The study outcomes support the prospect of ‘triple jeopardy’ for big bodied people through the intersection of discrimination, stigma and bias alongside social determinants of health and disaster vulnerability factors. Importantly, this study amplifies the voices of big bodied people, so often excluded, silenced or invisible in research. To meet the United Nation's Sendai Framework for Disaster Risk Reduction 2015–2030 requirement for ‘all-of-society engagement and partnership’, the conceptualisation of vulnerability must be widened to include size, shape and weight. Further empirical research and strong advocacy are required to ensure that big bodied people and emergency managers are well supported in preparedness planning and to ensure the needs of big bodied people are included in national and international in future disaster planning, policies and practices.