title: My journey with te reo Māori: From primary schooling in the mid 20th century to retirement from full-time academic service in the early years of the 21st Century

authors: Houia-Roberts, Ngaere

subjects: New Zealand

abstract: This is not an academic article in the traditional sense. It is a personal account of my experiences, as a first language speaker of te reo Māori, of New Zealand's educational system from the middle of the 20th century to the early years of the 21st century, from the early days of my primary schooling, through my service as a teacher, teacher trainer and academic researcher until my retirement from full-time academic service in 2005. A great deal has been written about the ways in which attitudes and approaches to te reo Māori have changed over that period of time but very little has been written about how it felt to be part of these changes. Our society is based on facts and feelings. If our mokopuna are to understand the fabric of our society, they need to have access to feelings as well as to facts. In this paper, weft and warp, facts and feelings, are woven together. This personal account is dedicated to our mokopuna, to all of our mokopuna, whatever their origin and whatever their colour. The future of our society depends upon their understanding.

text: My journey with te reo Māori: From primary schooling in the mid 20th century to retirement from full-time academic service in the early years of the 21st Century This is not an academic article in the traditional sense. It is a personal account of my experiences, as a first language speaker of te reo Māori, of New Zealand's educational system from the middle of the 20th century to the early years of the 21st century, from the early days of my primary schooling, through my service as a teacher, teacher trainer and academic researcher until my retirement from full-time academic service in 2005. A great deal has been written about the ways in which attitudes and approaches to te reo Māori have changed over that period of time but very little has been written about how it felt to be part of these changes. Our society is based on facts and feelings. If our mokopuna are to understand the fabric of our society, they need to have access to feelings as well as to facts. In this paper, weft and warp, facts and feelings, are woven together. This personal account is dedicated to our mokopuna, to all of our mokopuna, whatever their origin and whatever their colour. The future of our society depends upon their understanding.

year: 2006-02

title: He Pikinga Waiora: Supporting Maori health organisations to respond to pre-diabetes

authors: Beaton, Angela

subjects: Science & Technology

abstract: Background
Type 2 Diabetes (T2D) is a common long-term condition affecting the health and wellbeing of New Zealanders; one in every four New Zealanders is pre-diabetic. Māori, the Indigenous people of New Zealand, are at an increased risk of developing pre-diabetes and T2D and there are significant inequities between Māori and non-Māori for T2D complications. The purpose of this study was to explore the questions of how the strengths of Māori heath organisations may be leveraged, and how the barriers and constraints experienced by Māori health organisations may be negotiated, for the benefit of Māori; and from a systems perspective, to identify strategic opportunities that may be considered and applied by Māori health organisations, funders and policy makers to respond more effectively to pre-diabetes and reduce health inequities between Māori and non-Māori.

Methods
Utilising case study methodology, a range of data sources were triangulated including nine semi-structured interviews, documents, and a diabetes system map to identify possible strategic opportunities for key stakeholders to respond more effectively to pre-diabetes.

Results
Key themes and possible actions to improve health outcomes for Māori with pre-diabetes include: (1) Recognising Māori health organisations as conduits for the community voice and influential partners in the community to effect change; (2) Strengthened partnerships with Māori health organisations for community benefit and to support measurable, evidence-based change and service delivery, particularly when Māori knowledge systems are viewed alongside a Western scientific approach; and (3) Intersectoral integration of health and social services to support provision of whānau-centred care and influence the social determinants of health and local environment.
Conclusions
Māori health organisations are important actors in systems seeking to improve outcomes and eliminate health inequities. Support from funders and policy makers will be required to build on the strengths of these organisations and to overcome system challenges. To realise improved health outcomes for Māori, the value placed on whānau and community perspectives not only needs to be acknowledged in the implementation of health interventions, health and social policies and funding arrangements, but performance measures, service design and delivery must evolve to accommodate these perspectives in practice.

text: He Pikinga Waiora: Supporting Maori health organisations to respond to pre-diabetes Background
Type 2 Diabetes (T2D) is a common long-term condition affecting the health and wellbeing of New Zealanders; one in every four New Zealanders is pre-diabetic. Māori, the Indigenous people of New Zealand, are at an increased risk of developing pre-diabetes and T2D and there are significant inequities between Māori and non-Māori for T2D complications. The purpose of this study was to explore the questions of how the strengths of Māori heath organisations may be leveraged, and how the barriers and constraints experienced by Māori health organisations may be negotiated, for the benefit of Māori; and from a systems perspective, to identify strategic opportunities that may be considered and applied by Māori health organisations, funders and policy makers to respond more effectively to pre-diabetes and reduce health inequities between Māori and non-Māori.

Methods
Utilising case study methodology, a range of data sources were triangulated including nine semi-structured interviews, documents, and a diabetes system map to identify possible strategic opportunities for key stakeholders to respond more effectively to pre-diabetes.

Results
Key themes and possible actions to improve health outcomes for Māori with pre-diabetes include: (1) Recognising Māori health organisations as conduits for the community voice and influential partners in the community to effect change; (2) Strengthened partnerships with Māori health organisations for community benefit and to support measurable, evidence-based change and service delivery, particularly when Māori knowledge systems are viewed alongside a Western scientific approach; and (3) Intersectoral integration of health and social services to support provision of whānau-centred care and influence the social determinants of health and local environment.
Conclusions
Māori health organisations are important actors in systems seeking to improve outcomes and eliminate health inequities. Support from funders and policy makers will be required to build on the strengths of these organisations and to overcome system challenges. To realise improved health outcomes for Māori, the value placed on whānau and community perspectives not only needs to be acknowledged in the implementation of health interventions, health and social policies and funding arrangements, but performance measures, service design and delivery must evolve to accommodate these perspectives in practice.

year: 2019

title: Selected data exploration methods in hydroclimatology

authors: Vetrova, Varvara

subjects: hydrclimatology

abstract: The volumes of climatological data are rapidly growing due to development of new acquisition platforms and advances in data storage technologies. Such advances provide new challenging problems for data analysis methods. As a result, there is an increasing interest in application and development of new machine learning and data mining methods in climatological data analysis.

This dissertation contributes to the field of data analysis by evaluation of selected methods and developing new techniques with application to hydro-climatological datasets. 

It is shown that data pre-processing with the decimated wavelet discrete transform can cause false predictive accuracy in regression machine learning algorithms. A general result is obtained that a decimated wavelet discrete transform based on a pyramidal algorithm requires utilizing some future values of the time series concerned. When the discrete wavelet transform is utilized as a pre-processing step for forecasting the time series, the necessary independence of calibration and validation data is compromised. This in turn translates into over-optimistic forecasting accuracy or even giving the illusion of forecasting skill when there in none. The obtained result is general and has wide implications in any discipline where the discrete wavelet transform is utilised in forecasting frameworks.

In addition, a general framework for creating simple predictive models is presented, based on LASSO regularised regression. The method is illustrated for time series modelling with external event forcing but the approach has general applicability. 

As a contribution to association discovery, two tests of bivariate association are developed. The first method is designed for detecting threshold-like associations in a scatter plot with particular reference to testing the significance of the extent of a data-sparse region within a scatter plot. The second method is a more general test of non-random associations. Both methods utilise significance testing based on randomizations.

Finally, LASSO regularized regression is investigated as a tool for discovering informative large scale climatogical predictors of local hydrological processes. A cross-validation scheme is proposed, which is related to practical forecasts of the next time interval to come, while at the same time maximising use of available information. The proposed methodology was applied to a case study predicting next-season river discharges in the Upper Waitaki River in New Zealand. The proposed forecasting methodology and cross-validation frameworks are applicable for similar hydroclimatological forecasting situations. The physical aspect of this part of the study included discovering the influence of the Interdecadal Pacific Oscillation on winter discharges in the upper Waitaki catchment.

text: Selected data exploration methods in hydroclimatology The volumes of climatological data are rapidly growing due to development of new acquisition platforms and advances in data storage technologies. Such advances provide new challenging problems for data analysis methods. As a result, there is an increasing interest in application and development of new machine learning and data mining methods in climatological data analysis.

This dissertation contributes to the field of data analysis by evaluation of selected methods and developing new techniques with application to hydro-climatological datasets. 

It is shown that data pre-processing with the decimated wavelet discrete transform can cause false predictive accuracy in regression machine learning algorithms. A general result is obtained that a decimated wavelet discrete transform based on a pyramidal algorithm requires utilizing some future values of the time series concerned. When the discrete wavelet transform is utilized as a pre-processing step for forecasting the time series, the necessary independence of calibration and validation data is compromised. This in turn translates into over-optimistic forecasting accuracy or even giving the illusion of forecasting skill when there in none. The obtained result is general and has wide implications in any discipline where the discrete wavelet transform is utilised in forecasting frameworks.

In addition, a general framework for creating simple predictive models is presented, based on LASSO regularised regression. The method is illustrated for time series modelling with external event forcing but the approach has general applicability. 

As a contribution to association discovery, two tests of bivariate association are developed. The first method is designed for detecting threshold-like associations in a scatter plot with particular reference to testing the significance of the extent of a data-sparse region within a scatter plot. The second method is a more general test of non-random associations. Both methods utilise significance testing based on randomizations.

Finally, LASSO regularized regression is investigated as a tool for discovering informative large scale climatogical predictors of local hydrological processes. A cross-validation scheme is proposed, which is related to practical forecasts of the next time interval to come, while at the same time maximising use of available information. The proposed methodology was applied to a case study predicting next-season river discharges in the Upper Waitaki River in New Zealand. The proposed forecasting methodology and cross-validation frameworks are applicable for similar hydroclimatological forecasting situations. The physical aspect of this part of the study included discovering the influence of the Interdecadal Pacific Oscillation on winter discharges in the upper Waitaki catchment.

year: 2016