Journal of the Royal Society of New Zealand最新文献

This article presents a community-led kaupapa Māori research project involving Whakatōhea and neighbouring rohe (areas). This project arose from a moemoeā (dream or vision) of Tawhai, a stroke survivor who wanted to help fellow stroke survivors. We began with a survey of stroke survivors, community members and service providers in Ōpōtiki and surrounding areas, investigating community knowledge of stroke, barriers and facilitators to recovery, and the availability and appropriateness of health services for stroke survivors in the area. The ultimate aim was to facilitate Māori stroke survivors and whānau (family) to support recent stroke survivors, and find funding to allow sustainable employment of stroke survivors in this capacity. Survey results depicted an isolated community with very poor knowledge of stroke and little access to stroke services. However, they also revealed a community that is determined to look after their own, improve outcomes, and has the support of local health and social service providers. Community-based discussions on the survey results resulted in a vision for He Whare Oranga Tonutanga - a place where Māori stroke survivors and whānau could come to contribute what they can and take what they need. Māori stroke survivors could be employed to provide mentoring and run the centre.

Insufficient water for irrigation is a common problem in the Canterbury Region of New Zealand. Farmers have the option of applying for resource consent or joining a community irrigation scheme to take water. Water supply becomes more problematic during drought seasons as farmers must adhere to water restrictions imposed by the water authority. To deal with this problem, we developed an agent-based irrigation management system that can be used by farmers to calculate the ideal crop water needs on individual farms, which is particularly useful during periods of water scarcity. During water scarcity, most farms will have shortages of water. However, it is possible that there are farmers who will have excess water that could be distributed to those who need it. By doing this, farmers with excess water can make more profit and those who do not have enough water can purchase water to reduce their losses. In this work, we explore how auction-based negotiation in a multi-agent setting can be used to maximise water sharing within a community during periods of water scarcity. We evaluate various auction mechanisms that can be used to distribute excess water. In addition, we investigate the effect of various different agents' behaviours on water distribution and community profit.

ABSTRACT

The judiciary has historically been conservative in its use of Artificial Intelligence, but recent advances in machine learning have prompted scholars to reconsider such use in tasks like sentence prediction. This paper investigates by experimentation the potential use of explainable artificial intelligence for predicting imprisonment sentences in assault cases in New Zealand’s courts. We propose a proof-of-concept explainable model and verify in practice that it is fit for purpose, with predicted sentences accurate to within one year. We further analyse the model to understand the most influential phrases in sentence length prediction. We conclude the paper with an evaluative discussion of the future benefits and risks of different ways of using such an AI model in New Zealand’s courts.

Māori hold unique views on the lifecourse but there has been limited Māori-led longitudinal research to date. There is a particular need for kaupapa Māori and interface longitudinal research that generates mātauranga Māori and enables Māori-initiated transformative action. In this paper, we identify key features of a Māori lifecourse framework and its application to longitudinal research at the interface of mātauranga Māori and Western science. We describe how these features are applied in the Taranaki Māori-led longitudinal research programme Te Kura Mai i Tawhiti. Māori will benefit from a regionally-focussed Māori approach to lifecourse research at the interface. This approach can be applied directly in future localised research led by Māori and other Indigenous peoples. Māori-led longitudinal research will inform effective interventions to lift Māori wellbeing and prospects throughout all stages of life and strengthen Māori contributions to wider society. Māori approaches to longitudinal research will help shape new futures for Māori and a brighter future for all peoples of Aotearoa New Zealand. Glossary of Māori words: ao Māori: Māori world; Aotearoa: Māori name for New Zealand; hāngī: an earth oven or food cooked in such an oven; hapū: subtribe (also meaning to be pregnant); iwi: tribe, people; kaitiaki: guardian (also meaning teacher); kaupapa Māori: Māori paradigm; based within a Māori worldview; Māori: indigenous peoples of Aotearoa New Zealand; mātauranga Māori: Māori knowledge; mokopuna: grandchildren; ōhākī: parting wishes before death; Pākehā: primarily referring to New Zealand Europeans; reo Māori: Māori language; tamariki: children; Tangi te Kawekaweā: study title (the call of the kawekaweā, long-tailed cuckoo, heralds spring and the opportunity for growth); Taranaki: a tribal nation and region of Aotearoa New Zealand; Te Kura mai I Tawhiti: research programme title (sacred legacy of an ancient era); tauiwi: outsider, commonly referring to non-Māori; tuakiri: identity; wānanga: forum for sharing knowledge/learning; whakapapa: genealogy; whanau: extended family.

Proper management of the earth's natural resources is imperative to combat further degradation of the natural environment. However, the environmental datasets necessary for informed resource planning and conservation can be costly to collect and annotate. Consequently, there is a lack of publicly available datasets, particularly annotated image datasets relevant for environmental conservation, that can be used for the evaluation of machine learning algorithms to determine their applicability in real-world scenarios. To address this, the Time-evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) project in New Zealand aims to provide a collection of datasets and accompanying example notebooks for their analysis. This paper showcases three New Zealand-based annotated image datasets that form part of the collection. The first dataset contains annotated images of various predator species, mainly small invasive mammals, taken using low-light camera traps predominantly at night. The second provides aerial photography of the Waikato region in New Zealand, in which stands of Kahikatea (a native New Zealand tree) have been marked up using manual segmentation. The third is a dataset containing orthorectified high-resolution aerial photography, paired with satellite imagery taken by Sentinel-2. Additionally, the TAIAO web platform also contains a collated list of other datasets provided and licensed by our data partners that may be of interest to other researchers.

Aotearoa New Zealand's response to the COVID-19 pandemic has included the use of algorithms that could aid decision making. Te Pokapū Hātepe o Aotearoa, the New Zealand Algorithm Hub, was established to evaluate and host COVID-19 related models and algorithms, and provide a central and secure infrastructure to support the country's pandemic response. A critical aspect of the Hub was the formation of an appropriate governance group to ensure that algorithms being deployed underwent cross-disciplinary scrutiny prior to being made available for quick and safe implementation. This framework necessarily canvassed a broad range of perspectives, including from data science, clinical, Māori, consumer, ethical, public health, privacy, legal and governmental perspectives. To our knowledge, this is the first implementation of national algorithm governance of this type, building upon broad local and global discussion of guidelines in recent years. This paper describes the experiences and lessons learned through this process from the perspective of governance group members, emphasising the role of robust governance processes in building a high-trust platform that enables rapid translation of algorithms from research to practice.

Over the last 50 years Dunedin Study researchers have published more than 1400 peer-reviewed journal articles, books, and reports on many aspects of human health and development. In this 50th anniversary piece we reflect on (i) our historical roots and necessary re-invention through time; (ii) the underpinning principles that have contributed to our success; (iii) some selected examples of high-impact work from the behavioural, oral health, and respiratory domains; (iv) some of the challenges we have encountered over time and how to overcome these; and (vi) review where we see the Study going in the future. We aim to present some of the 'back story', which is typically undocumented and oft lost to memory, and thus focus on 'know-how'. Our hope is to humanise our research, share insights, and to acknowledge the real heroes of the Study - the 1037 Study members, their families and their friends, who have collectively given so much, for so long, in the hope of helping others.