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Audio, Radio New Zealand

This week marked the 4th anniversary of the Christchurch and Canterbury earthquake. New research from the University of Otago in Christchurch with earthquake survivors is shedding some light on the question of what makes some people cope better with trauma than others. A group of psychiatrists and psychologists from the University have been studying a group of more than 100 Cantabrians exposed to high levels of stress during the earthquakes who coped well. They compared this group against a group of patients with post-earthquake trauma, being treated by the Adult Specialist Services Earthquake Treatment Team, or ASSETT, set up by the Canterbury DHB. Dr Gini McIntosh from the Otago University is part of the research team, and one of the psychologists with ASSETT.

Research papers, University of Canterbury Library

SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database.

Research papers, University of Canterbury Library

Overview of SeisFinder SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database. The basic SeisFinder architecture is shown in Figure 1.

Research papers, University of Canterbury Library

There are many things that organisations of any size can do to prepare for a disaster or crisis. Traditionally, the advice given to business has focused on identifying risks, reducing their likely occurrence, and planning in advance how to respond. More recently, there is growing interest in the broader concept of organisational resilience which includes planning for crisis but also considers traits that lead to organisational adaptability and ability to thrive despite adverse circumstances. In this paper we examine the policy frameworks1 within New Zealand that influence the resilience of small and medium sized businesses (SMEs). The first part of the paper focuses on the New Zealand context, including the prevailing political and economic ideologies, the general nature of New Zealand SMEs and the nature of New Zealand’s hazard environment. The paper then goes on to outline the key policy frameworks in place relevant to SMEs and hazards. The final part of the paper examines the way the preexisting policy environment influenced the response of SMEs and Government following the Canterbury earthquakes.