The purpose of this research is to investigate men’s experiences of the 2016 7.8 magnitude Kaikōura earthquake and Tsunami. While, research into the impacts of the earthquake has been conducted, few studies have examined how gender shaped people’s experiences of this natural hazard event. Analysing disasters through a gender lens has significantly contributed to disaster scholarship in identifying the resilience and vulnerabilities of individuals and communities pre- and post-disaster (Fordham, 2012; Bradshaw, 2013). This research employs understandings of masculinities (Connell, 2005), to examine men’s strengths and challenges in responding, recovering, and coping following the earthquake. Qualitative inquiry was carried out in Northern Canterbury and Marlborough involving 18 face-to-face interviews with men who were impacted by the Kaikōura earthquake and its aftermath. Interview material is being analysed using thematic and narrative analysis. Some of the preliminary findings have shown that men took on voluntary roles in addition to their fulltime paid work resulting in long hours, poor sleep and little time spent with family. Some men assisted wives and children to high ground then drove into the tsunami zone to check on relatives or to help evacuate people. Although analysis of the findings is currently ongoing, preliminary findings have identified that the men who participated in the study have been negatively impacted by the 2016 Kaikōura earthquake. A theme identified amongst participants was an avoidance to seek support with the challenges they were experiencing due to the earthquake. The research findings align with key characteristics of masculinity, including demonstrating risky behaviours and neglecting self or professional care. This study suggests that these behaviours affect men’s overall resilience, and thus the resilience of the wider community.
Earthquake-triggered soil liquefaction caused extensive damage and heavy economic losses in Christchurch during the 2010-2011 Canterbury earthquakes. The most severe manifestations of liquefaction were associated with the presence of natural deposits of clean sands and silty sands of fluvial origin. However, liquefaction resistance of fines-containing sands is commonly inferred from empirical relationships based on clean sands (i.e. sands with less than 5% fines). Hence, existing evaluation methods have poor accuracy when applied to silty sands. Also, existing methods do not quantify appropriately the influence on liquefaction resistance of soil fabric and structure, which are unique to a specific depositional environment. This study looks at the influence of fines content, soil fabric (i.e. arrangement of soil particles) and structure (e.g. layering, segregation) on the undrained cyclic behaviour and liquefaction resistance of fines-containing sandy soils from Christchurch using Direct Simple Shear (DSS) tests on soil specimens reconstituted in the laboratory with the water sedimentation technique. The poster describes experimental procedures and presents early test results on two sands retrieved at two different sites in Christchurch.
Natural catastrophes are increasing worldwide. They are becoming more frequent but also more severe and impactful on our built environment leading to extensive damage and losses. Earthquake events account for the smallest part of natural events; nevertheless seismic damage led to the most fatalities and significant losses over the period 1981-2016 (Munich Re). Damage prediction is helpful for emergency management and the development of earthquake risk mitigation projects. Recent design efforts focused on the application of performance-based design engineering where damage estimation methodologies use fragility and vulnerability functions. However, the approach does not explicitly specify the essential criteria leading to economic losses. There is thus a need for an improved methodology that finds the critical building elements related to significant losses. The here presented methodology uses data science techniques to identify key building features that contribute to the bulk of losses. It uses empirical data collected on site during earthquake reconnaissance mission to train a machine learning model that can further be used for the estimation of building damage post-earthquake. The first model is developed for Christchurch. Empirical building damage data from the 2010-2011 earthquake events is analysed to find the building features that contributed the most to damage. Once processed, the data is used to train a machine-learning model that can be applied to estimate losses in future earthquake events.
Research indicates that aside from the disaster itself, the next major source of adverse outcomes during such events, is from errors by either the response leader or organisation. Yet, despite their frequency, challenge, complexity, and the risks involved; situations of extreme context remain one of the least researched areas in the leadership field. This is perhaps surprising. In the 2010 and 2011 (Christchurch) earthquakes alone, 185 people died and rebuild costs are estimated to have been $40b. Add to this the damage and losses annually around the globe arising from natural disasters, major business catastrophes, and military conflict; there is certainly a lot at stake (lives, way of life, and our well-being). While over the years, much has been written on leadership, there is a much smaller subset of articles on leadership in extreme contexts, with the majority of these focusing on the event rather than leadership itself. Where leadership has been the focus, the spotlight has shone on the actions and capabilities of one person - the leader. Leadership, however, is not simply one person, it is a chain or network of people, delivering outcomes with the support of others, guided by a governance structure, contextualised by the environment, and operating on a continuum across time (before, during, and after an event). This particular research is intended to examine the following: • What are the leadership capabilities and systems necessary to deliver more successful outcomes during situations of extreme context; • How does leadership in these circumstances differ from leadership during business as usual conditions; • Lastly, through effective leadership, can we leverage these unfortunate events to thrive, rather than merely survive?
