title: Supervision as cultural partnership: Contributions to dialogue

authors: Crocket, Kathie

abstract: The term cultural supervision has been coined as part of a strategy that implicates supervision in the support and development of culturally appropriate therapeutic practice. In Aotearoa New Zealand particular focus has been given to supervision where the client is Māori and the practitioner is a member of the dominant Pākehā culture particularly, or of other non-Māori cultures. However, while the phrase cultural supervision has entered common professional parlance, the practice has had little research attention in counselling/psychotherapy in New Zealand. Cultural supervision appears to encompass a range of understandings, and there is no clear agreement about practice implications. It is unclear what alignment there is between aspirations, regulations, and practice. This article reports on an exploratory qualitative study that investigated how supervision might work in supporting culturally appropriate counselling practice in Aotearoa New Zealand. The study’s findings are presented as a multi-voiced dialogue. This arts-based representational practice enacts the uncertainties of post-colonial experience. Its intention is to make assumptions, ideas, and practices available for discussion. Its contribution is to join current dialogue about supervision and culture, and to raise further questions about how supervision and culturally appropriate practice come together.

text: Supervision as cultural partnership: Contributions to dialogue The term cultural supervision has been coined as part of a strategy that implicates supervision in the support and development of culturally appropriate therapeutic practice. In Aotearoa New Zealand particular focus has been given to supervision where the client is Māori and the practitioner is a member of the dominant Pākehā culture particularly, or of other non-Māori cultures. However, while the phrase cultural supervision has entered common professional parlance, the practice has had little research attention in counselling/psychotherapy in New Zealand. Cultural supervision appears to encompass a range of understandings, and there is no clear agreement about practice implications. It is unclear what alignment there is between aspirations, regulations, and practice. This article reports on an exploratory qualitative study that investigated how supervision might work in supporting culturally appropriate counselling practice in Aotearoa New Zealand. The study’s findings are presented as a multi-voiced dialogue. This arts-based representational practice enacts the uncertainties of post-colonial experience. Its intention is to make assumptions, ideas, and practices available for discussion. Its contribution is to join current dialogue about supervision and culture, and to raise further questions about how supervision and culturally appropriate practice come together.

year: 2015

title: My tūpuna were houseless once too: Aspirations of ‘home’ for rangatahi Māori in transitional housing

authors: Manuirirangi, Kayla

abstract: This research explores the concept of ‘home' for rangatahi Māori experiencing housing insecurity and residing within a transitional housing service in Kirikiriroa, Hamilton. Conducted in partnership with Kirikiriroa Family Services Trust (KFST), a kaupapa Māori community housing provider, this study aimed to identify rangatahi perceptions of ‘home’ and aspirations of 'home’ to contribute towards strategies for better housing supports and brighter rangatahi futures. A cohort of seven rangatahi Māori participants were involved in this study (all who identified as female; aged 15-19 years old). At the time of this study, rangatahi participants were residing in Kirikiriroa, experiencing housing insecurity and were living within a transitional house provided by KFST, either with whānau or independently. Guided by Kaupapa Māori methodology, there were a mixture of qualitative methods used to capture rangatahi voices, including Whakawhanaungatanga, Sticky Notes Brainstorms, Rangatahi Wānanga and Thematic Analysis. Through this data analysis process, a visual mind map was generated to draw out the key findings from the three main research areas: rangatahi aspirations for home; the current realities of home; and how to build a bridge to a better future. Key findings from this research conclude that: (1) Rangatahi need strength-based support; (2) Rangatahi need a permanent and stable place to call ‘home’; (3) Rangatahi need supportive adults in their life who they can trust; (4) Rangatahi need encouragement to realise their aspirations; (5) Rangatahi opinions matter; (6) Rangatahi experience contradictions; and, the need to (7) Prioritise intervention over punishment. For policy and decision-makers, these findings suggest that rangatahi Māori voices should be included in urban design process and that more Māori solutions should be utilised within this urban context. For researchers, the study highlights the importance of advancing Māori housing aspirations and deepening understandings of ‘home’ for rangatahi Māori living independent of their whānau.

text: My tūpuna were houseless once too: Aspirations of ‘home’ for rangatahi Māori in transitional housing This research explores the concept of ‘home' for rangatahi Māori experiencing housing insecurity and residing within a transitional housing service in Kirikiriroa, Hamilton. Conducted in partnership with Kirikiriroa Family Services Trust (KFST), a kaupapa Māori community housing provider, this study aimed to identify rangatahi perceptions of ‘home’ and aspirations of 'home’ to contribute towards strategies for better housing supports and brighter rangatahi futures. A cohort of seven rangatahi Māori participants were involved in this study (all who identified as female; aged 15-19 years old). At the time of this study, rangatahi participants were residing in Kirikiriroa, experiencing housing insecurity and were living within a transitional house provided by KFST, either with whānau or independently. Guided by Kaupapa Māori methodology, there were a mixture of qualitative methods used to capture rangatahi voices, including Whakawhanaungatanga, Sticky Notes Brainstorms, Rangatahi Wānanga and Thematic Analysis. Through this data analysis process, a visual mind map was generated to draw out the key findings from the three main research areas: rangatahi aspirations for home; the current realities of home; and how to build a bridge to a better future. Key findings from this research conclude that: (1) Rangatahi need strength-based support; (2) Rangatahi need a permanent and stable place to call ‘home’; (3) Rangatahi need supportive adults in their life who they can trust; (4) Rangatahi need encouragement to realise their aspirations; (5) Rangatahi opinions matter; (6) Rangatahi experience contradictions; and, the need to (7) Prioritise intervention over punishment. For policy and decision-makers, these findings suggest that rangatahi Māori voices should be included in urban design process and that more Māori solutions should be utilised within this urban context. For researchers, the study highlights the importance of advancing Māori housing aspirations and deepening understandings of ‘home’ for rangatahi Māori living independent of their whānau.

year: 2025

title: Machine learning in practice: experience with agricultural databases

authors: Garner, Stephen R.

subjects: computer science

abstract: The Waikato Environment for Knowledge Analysis (weka) is a New Zealand government-sponsored initiative to investigate the application of machine learning to economically important problems in the agricultural industries. The overall goals are to create a workbench for machine learning, determine the factors that contribute towards its successful application in the agricultural industries, and develop new methods of machine learning and ways of assessing their effectiveness. The project began in 1993 and is currently working towards the fulfilment of three objectives: to design and implement the workbench, to provide case studies of applications of machine learning techniques to problems in agriculture, and to develop a methodology for evaluating generalisations in terms of their entropy. These three objectives are by no means independent. For example, the design of the weka workbench has been inspired by the demands placed on it by the case studies, and has also benefited from our work on evaluating the outcomes of applying a technique to data. Our experience throughout the development of the project is that the successful application of machine learning involves much more than merely executing a learning algorithm on some data. In this paper we present the process model that underpins our work over the past two years for the development of applications in agriculture; the software we have developed around our workbench of machine learning schemes to support this model; and the outcomes and problems we have encountered in developing applications.

text: Machine learning in practice: experience with agricultural databases The Waikato Environment for Knowledge Analysis (weka) is a New Zealand government-sponsored initiative to investigate the application of machine learning to economically important problems in the agricultural industries. The overall goals are to create a workbench for machine learning, determine the factors that contribute towards its successful application in the agricultural industries, and develop new methods of machine learning and ways of assessing their effectiveness. The project began in 1993 and is currently working towards the fulfilment of three objectives: to design and implement the workbench, to provide case studies of applications of machine learning techniques to problems in agriculture, and to develop a methodology for evaluating generalisations in terms of their entropy. These three objectives are by no means independent. For example, the design of the weka workbench has been inspired by the demands placed on it by the case studies, and has also benefited from our work on evaluating the outcomes of applying a technique to data. Our experience throughout the development of the project is that the successful application of machine learning involves much more than merely executing a learning algorithm on some data. In this paper we present the process model that underpins our work over the past two years for the development of applications in agriculture; the software we have developed around our workbench of machine learning schemes to support this model; and the outcomes and problems we have encountered in developing applications.

year: 1995-05