scholarly journals Record linkage on Māori land data to find and connect the missing

2021 ◽  
Author(s):  
◽  
Valerie Chan

<p>We consider probabilistic modelling for accomplishing record linkage across two large scale publicly available data sources: New Zealand Births Deaths and Marriages (BDM), and Māori Land Online (MLO). We undertake this project in the context of te ao Māori, integrating mātauranga Māori principles into the work. We present several methods for record linkage and several novel ways to reject false linkages.</p>

2021 ◽  
Author(s):  
◽  
Valerie Chan

<p>We consider probabilistic modelling for accomplishing record linkage across two large scale publicly available data sources: New Zealand Births Deaths and Marriages (BDM), and Māori Land Online (MLO). We undertake this project in the context of te ao Māori, integrating mātauranga Māori principles into the work. We present several methods for record linkage and several novel ways to reject false linkages.</p>


1969 ◽  
Vol 08 (01) ◽  
pp. 07-11 ◽  
Author(s):  
H. B. Newcombe

Methods are described for deriving personal and family histories of birth, marriage, procreation, ill health and death, for large populations, from existing civil registrations of vital events and the routine records of ill health. Computers have been used to group together and »link« the separately derived records pertaining to successive events in the lives of the same individuals and families, rapidly and on a large scale. Most of the records employed are already available as machine readable punchcards and magnetic tapes, for statistical and administrative purposes, and only minor modifications have been made to the manner in which these are produced.As applied to the population of the Canadian province of British Columbia (currently about 2 million people) these methods have already yielded substantial information on the risks of disease: a) in the population, b) in relation to various parental characteristics, and c) as correlated with previous occurrences in the family histories.


2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Catherine M. Febria ◽  
Maggie Bayfield ◽  
Kathryn E. Collins ◽  
Hayley S. Devlin ◽  
Brandon C. Goeller ◽  
...  

In Aotearoa New Zealand, agricultural land-use intensification and decline in freshwater ecosystem integrity pose complex challenges for science and society. Despite riparian management programmes across the country, there is frustration over a lack in widespread uptake, upfront financial costs, possible loss in income, obstructive legislation and delays in ecological recovery. Thus, social, economic and institutional barriers exist when implementing and assessing agricultural freshwater restoration. Partnerships are essential to overcome such barriers by identifying and promoting co-benefits that result in amplifying individual efforts among stakeholder groups into coordinated, large-scale change. Here, we describe how initial progress by a sole farming family at the Silverstream in the Canterbury region, South Island, New Zealand, was used as a catalyst for change by the Canterbury Waterway Rehabilitation Experiment, a university-led restoration research project. Partners included farmers, researchers, government, industry, treaty partners (Indigenous rights-holders) and practitioners. Local capacity and capability was strengthened with practitioner groups, schools and the wider community. With partnerships in place, co-benefits included lowered costs involved with large-scale actions (e.g., earth moving), reduced pressure on individual farmers to undertake large-scale change (e.g., increased participation and engagement), while also legitimising the social contracts for farmers, scientists, government and industry to engage in farming and freshwater management. We describe contributions and benefits generated from the project and describe iterative actions that together built trust, leveraged and aligned opportunities. These actions were scaled from a single farm to multiple catchments nationally.


Epidemiologia ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 315-324
Author(s):  
Juan M. Banda ◽  
Ramya Tekumalla ◽  
Guanyu Wang ◽  
Jingyuan Yu ◽  
Tuo Liu ◽  
...  

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated on the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique worldwide event in biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 1.12 billion tweets, growing daily, related to COVID-19 chatter generated from 1 January 2020 to 27 June 2021 at the time of writing. This data source provides a freely available additional data source for researchers worldwide to conduct a wide and diverse number of research projects, such as epidemiological analyses, emotional and mental responses to social distancing measures, the identification of sources of misinformation, stratified measurement of sentiment towards the pandemic in near real time, among many others.


2004 ◽  
Vol 31 (3) ◽  
pp. 319 ◽  
Author(s):  
Jane Catherine Kitson

Sooty shearwaters (tītī, muttonbird, Puffinus griseus) are highly abundant migratory seabirds, which return to breeding colonies in New Zealand. The Rakiura Māori annual chick harvest on islands adjacent to Rakiura (Stewart Island), is one of the last large-scale customary uses of native wildlife in New Zealand. This study aimed to establish whether the rate at which muttonbirders can extract chicks from their breeding burrows indicates population trends of sooty shearwaters. Harvest rates increased slightly with increasing chick densities on Putauhinu Island. Birders' harvest rates vary in their sensitivities to changing chick density. Therefore a monitoring panel requires careful screening to ensure that harvest rates of the birders selected are sensitive to chick density, and represents a cross-section of different islands. Though harvest rates can provide only a general index of population change, it can provide an inexpensive and feasible way to measure population trends. Detecting trends is the first step to assessing the long-term sustainability of the harvest.


Author(s):  
Carla Houkamau ◽  
Petar Milojev ◽  
Lara Greaves ◽  
Kiri Dell ◽  
Chris G Sibley ◽  
...  

AbstractLongitudinal studies into the relationship between affect (positive or negative feelings) towards one’s own ethnic group and wellbeing are rare, particularly for Indigenous peoples. In this paper, we test the longitudinal effects of in-group warmth (a measure of ethnic identity affect) and ethnic identity centrality on three wellbeing measures for New Zealand Māori: life satisfaction (LS), self-esteem (SE), and personal wellbeing (PW). Longitudinal panel data collected from Māori (N = 3803) aged 18 or over throughout seven annual assessments (2009–2015) in the New Zealand Attitudes and Values Study were analyzed using latent trajectory models with structured residuals to examine cross-lagged within-person effects. Higher in-group warmth towards Māori predicted increases in all three wellbeing measures, even more strongly than ethnic identity centrality. Bi-directionally, PW and SE predicted increased in-group warmth, and SE predicted ethnic identification. Further, in sample-level (between-person) trends, LS and PW rose, but ethnic identity centrality interestingly declined over time. This is the first large-scale longitudinal study showing a strong relationship between positive affect towards one’s Indigenous ethnic group and wellbeing. Efforts at cultural recovery and restoration have been a deliberate protective response to colonization, but among Māori, enculturation and access to traditional cultural knowledge varies widely. The data reported here underline the role of ethnic identity affect as an important dimension of wellbeing and call for continued research into the role of this dimension of ethnic identity for Indigenous peoples.


2020 ◽  
Vol 14 (3) ◽  
pp. 320-328
Author(s):  
Long Guo ◽  
Lifeng Hua ◽  
Rongfei Jia ◽  
Fei Fang ◽  
Binqiang Zhao ◽  
...  

With the rapid growth of e-commerce in recent years, e-commerce platforms are becoming a primary place for people to find, compare and ultimately purchase products. To improve online shopping experience for consumers and increase sales for sellers, it is important to understand user intent accurately and be notified of its change timely. In this way, the right information could be offered to the right person at the right time. To achieve this goal, we propose a unified deep intent prediction network, named EdgeDIPN, which is deployed at the edge, i.e., mobile device, and able to monitor multiple user intent with different granularity simultaneously in real-time. We propose to train EdgeDIPN with multi-task learning, by which EdgeDIPN can share representations between different tasks for better performance and saving edge resources in the meantime. In particular, we propose a novel task-specific attention mechanism which enables different tasks to pick out the most relevant features from different data sources. To extract the shared representations more effectively, we utilize two kinds of attention mechanisms, where the multi-level attention mechanism tries to identify the important actions within each data source and the inter-view attention mechanism learns the interactions between different data sources. In the experiments conducted on a large-scale industrial dataset, EdgeDIPN significantly outperforms the baseline solutions. Moreover, EdgeDIPN has been deployed in the operational system of Alibaba. Online A/B testing results in several business scenarios reveal the potential of monitoring user intent in real-time. To the best of our knowledge, EdgeDIPN is the first full-fledged real-time user intent understanding center deployed at the edge and serving hundreds of millions of users in a large-scale e-commerce platform.


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