title: Geothermal energy, decarbonisation and the just transition: developments in governance and regulation

authors: Parson, Phoebe

abstract: This review article pursues this special issue’s theme of renewable energy and just transition into the field of geothermal energy, an energy source which has a special role in Aotearoa New Zealand, and which raises clear questions of justice in the energy transition. It evaluates the track record, and examines the legal, regulatory and institutional challenges and opportunities for a just transition for geothermal in New Zealand. It particularly considers the role of Māori, and the challenges presented by emerging technological change. It considers the problems of renewability and sustainability that are special to geothermal resources. It evaluates the just transition issues that have particularly affected Māori landowners and holders of mana whenua. It finds that what constitutes a just transition must be seen against a longer historical time frame than many observers might assume. It shows that the distinctive regulatory framework for geothermal has been considerably affected by addressing these problems but may need to adapt further in the future. It considers the technical features that have shaped geothermal regulation and are likely to shape it in the future as new technological options emerge.

text: Geothermal energy, decarbonisation and the just transition: developments in governance and regulation This review article pursues this special issue’s theme of renewable energy and just transition into the field of geothermal energy, an energy source which has a special role in Aotearoa New Zealand, and which raises clear questions of justice in the energy transition. It evaluates the track record, and examines the legal, regulatory and institutional challenges and opportunities for a just transition for geothermal in New Zealand. It particularly considers the role of Māori, and the challenges presented by emerging technological change. It considers the problems of renewability and sustainability that are special to geothermal resources. It evaluates the just transition issues that have particularly affected Māori landowners and holders of mana whenua. It finds that what constitutes a just transition must be seen against a longer historical time frame than many observers might assume. It shows that the distinctive regulatory framework for geothermal has been considerably affected by addressing these problems but may need to adapt further in the future. It considers the technical features that have shaped geothermal regulation and are likely to shape it in the future as new technological options emerge.

year: 2025

title: Te Rau Matatini: Māori mental health workforce
development

authors: Hirini, Paul

subjects: Maori

abstract: Outlines the development and current projects of Te Rau Matatini, a charitable trust aiming to strengthen the Maori mental health workforce.

text: Te Rau Matatini: Māori mental health workforce
development Outlines the development and current projects of Te Rau Matatini, a charitable trust aiming to strengthen the Maori mental health workforce.

year: 2003

title: Interactive machine learning–letting users build classifiers

authors: Ware, Malcolm

subjects: computer science

abstract: According to standard procedure, building a classifier is a fully automated process that follows data preparation by a domain expert. In contrast, interactive machine learning engages users in actually generating the classifier themselves. This offers a natural way of integrating background knowledge into the modeling stage–so long as interactive tools can be designed that support efficient and effective communication. This paper shows that appropriate techniques can empower users to create models that compete with classifiers built by state-of-the-art learning algorithms. It demonstrates that users–even users who are not domain experts–can often construct good classifiers, without any help from a learning algorithm, using a simple two-dimensional visual interface. Experiments demonstrate that, not surprisingly, success hinges on the domain: if a few attributes can support good predictions, users generate accurate classifiers, whereas domains with many high-order attribute interactions favor standard machine learning techniques. The future challenge is to achieve a symbiosis between human user and machine learning algorithm.

text: Interactive machine learning–letting users build classifiers According to standard procedure, building a classifier is a fully automated process that follows data preparation by a domain expert. In contrast, interactive machine learning engages users in actually generating the classifier themselves. This offers a natural way of integrating background knowledge into the modeling stage–so long as interactive tools can be designed that support efficient and effective communication. This paper shows that appropriate techniques can empower users to create models that compete with classifiers built by state-of-the-art learning algorithms. It demonstrates that users–even users who are not domain experts–can often construct good classifiers, without any help from a learning algorithm, using a simple two-dimensional visual interface. Experiments demonstrate that, not surprisingly, success hinges on the domain: if a few attributes can support good predictions, users generate accurate classifiers, whereas domains with many high-order attribute interactions favor standard machine learning techniques. The future challenge is to achieve a symbiosis between human user and machine learning algorithm.

year: 2000-03