title: Teacher attrition from coaching in New Zealand Secondary Schools

authors: Pope, Clive C.

abstract: This report outlines the findings from the School Sport NZ research project undertaken by the University of Waikato during the period of September 2018 – August 2019. This Executive Summary details a brief overview of the background for the project, the design/methodology adopted for the research and a summary of the findings from the three phases of the research project. The results are presented with an enmeshing of both survey and interview data. Reference has been made to relevant documentation and/or research and pertinent literature where deemed appropriate

text: Teacher attrition from coaching in New Zealand Secondary Schools This report outlines the findings from the School Sport NZ research project undertaken by the University of Waikato during the period of September 2018 – August 2019. This Executive Summary details a brief overview of the background for the project, the design/methodology adopted for the research and a summary of the findings from the three phases of the research project. The results are presented with an enmeshing of both survey and interview data. Reference has been made to relevant documentation and/or research and pertinent literature where deemed appropriate

year: 2020

title: Discriminant function analysis of late Quaternary tephras from five volcanoes in New Zealand using glass shard major element chemistry

authors: Stokes, Stephen

subjects: tephra

abstract: The microprobe-determined glass shard major element chemistry of tephras derived from five North Island, New Zealand volcanoes (Mayor Island, Okataina, Taupo, Tongariro, and Mount Egmont) and younger than ca. 20,000 yr B.P. was subjected to discriminant function analysis. Four separate approaches were adopted to test the match of the tephras with their known sources: (1) an analysis of raw microprobe data; (2) an analysis of normalized data; (3) an analysis of the data transformed by calculating the log10 of oxide scores divided (arbitrarily) by the chlorine content; and (4) a repeat of (3) with multivariate outlier scores, as determined by principal components analysis, deleted. All yielded excellent classification functions (efficiencies of 91–100%), with the eruptives associated with each of the five volcanoes being chemically distinct from one another. In each approach, the first two canonical discriminant functions accounted for >90% of the variation between groups. The removal of multivariate outliers from the data set had only minor effects on the performance of the discriminant function procedures. Separate discriminant function analysis of the relatively alike Taupo and Okataina eruptives gave a greater degree of multivariate separation. The numerical classifications generated should enable unidentified tephras erupted since ca. 20,000 yr B.P. from the five volcanoes to be provisionally matched with their sources.

text: Discriminant function analysis of late Quaternary tephras from five volcanoes in New Zealand using glass shard major element chemistry The microprobe-determined glass shard major element chemistry of tephras derived from five North Island, New Zealand volcanoes (Mayor Island, Okataina, Taupo, Tongariro, and Mount Egmont) and younger than ca. 20,000 yr B.P. was subjected to discriminant function analysis. Four separate approaches were adopted to test the match of the tephras with their known sources: (1) an analysis of raw microprobe data; (2) an analysis of normalized data; (3) an analysis of the data transformed by calculating the log10 of oxide scores divided (arbitrarily) by the chlorine content; and (4) a repeat of (3) with multivariate outlier scores, as determined by principal components analysis, deleted. All yielded excellent classification functions (efficiencies of 91–100%), with the eruptives associated with each of the five volcanoes being chemically distinct from one another. In each approach, the first two canonical discriminant functions accounted for >90% of the variation between groups. The removal of multivariate outliers from the data set had only minor effects on the performance of the discriminant function procedures. Separate discriminant function analysis of the relatively alike Taupo and Okataina eruptives gave a greater degree of multivariate separation. The numerical classifications generated should enable unidentified tephras erupted since ca. 20,000 yr B.P. from the five volcanoes to be provisionally matched with their sources.

year: 1988

title: Indigenous data sovereignty

authors: Kukutai, Tahu

abstract: Indigenous Peoples have always been ‘data warriors’. Our ancient traditions recorded and protected information and knowledge through art, carving, song, chants and other practises. Deliberate efforts to expunge these knowledge systems were part and parcel of colonisation, along with state-imposed practices of counting and classifying Indigenous populations. As a result, Indigenous Peoples often encounter severe data deficits when trying to access high quality, culturally relevant data to pursue their goals, but an abundance of data that reflects and serves government interests regarding Indigenous Peoples and their lands. 
The concept of Indigenous data sovereignty (ID-SOV) is a relatively recent one, with the first major publication on the topic only appearing in 2016.1 ID-SOV is defined as the right of Indigenous Peoples to own, control, access and possess data that derive from them, and which pertain to their members, knowledge systems, customs or territories.2,3,4 ID-SOV is supported by Indigenous Peoples’ inherent rights of self-determination and governance over their peoples, territories and resources as affirmed in the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), as well as in domestic treaties. ID-SOV recognises that data is a strategic resource and provides a framework for the ethical use of data to advance collective Indigenous wellbeing and self-determination.5,6 In practice ID-Sov means that Indigenous Peoples need to be the decision-makers around how data about them are used.
Given that most Indigenous data is not in the possession of Indigenous Peoples, Indigenous data governance (ID-GOV) is seen as a key lever for addressing ID-SOV. ID-GOV harnesses Indigenous Peoples’ values, rights and interests to guide decision-making about how their data are collected, accessed, stored, and used.7 Enacting ID-GOV results in Indigenous control of Indigenous data through both internal Indigenous community data governance policies and practices and external stewardship of Indigenous data via mechanisms and frameworks that reflect Indigenous values.

text: Indigenous data sovereignty Indigenous Peoples have always been ‘data warriors’. Our ancient traditions recorded and protected information and knowledge through art, carving, song, chants and other practises. Deliberate efforts to expunge these knowledge systems were part and parcel of colonisation, along with state-imposed practices of counting and classifying Indigenous populations. As a result, Indigenous Peoples often encounter severe data deficits when trying to access high quality, culturally relevant data to pursue their goals, but an abundance of data that reflects and serves government interests regarding Indigenous Peoples and their lands. 
The concept of Indigenous data sovereignty (ID-SOV) is a relatively recent one, with the first major publication on the topic only appearing in 2016.1 ID-SOV is defined as the right of Indigenous Peoples to own, control, access and possess data that derive from them, and which pertain to their members, knowledge systems, customs or territories.2,3,4 ID-SOV is supported by Indigenous Peoples’ inherent rights of self-determination and governance over their peoples, territories and resources as affirmed in the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), as well as in domestic treaties. ID-SOV recognises that data is a strategic resource and provides a framework for the ethical use of data to advance collective Indigenous wellbeing and self-determination.5,6 In practice ID-Sov means that Indigenous Peoples need to be the decision-makers around how data about them are used.
Given that most Indigenous data is not in the possession of Indigenous Peoples, Indigenous data governance (ID-GOV) is seen as a key lever for addressing ID-SOV. ID-GOV harnesses Indigenous Peoples’ values, rights and interests to guide decision-making about how their data are collected, accessed, stored, and used.7 Enacting ID-GOV results in Indigenous control of Indigenous data through both internal Indigenous community data governance policies and practices and external stewardship of Indigenous data via mechanisms and frameworks that reflect Indigenous values.

year: 2020