title: Restorative Practices in Schools: Far-Reaching Implications

authors: Drewery, Wendy

subjects: New Zealand

abstract: In 1999, the New Zealand Ministry of Education contracted a team from the University of Waikato to develop a process for conferencing in schools. The brief was to utilise restorative justice principles to develop a conferencing process for use in schools. The purpose was to test whether such an approach to wrongdoing could reduce the exponential increase of suspensions, particularly of Maori boys, who were, and still are, disproportionately represented in reported numbers of suspensions, stand-downs and exclusions.

text: Restorative Practices in Schools: Far-Reaching Implications In 1999, the New Zealand Ministry of Education contracted a team from the University of Waikato to develop a process for conferencing in schools. The brief was to utilise restorative justice principles to develop a conferencing process for use in schools. The purpose was to test whether such an approach to wrongdoing could reduce the exponential increase of suspensions, particularly of Maori boys, who were, and still are, disproportionately represented in reported numbers of suspensions, stand-downs and exclusions.

year: 2007

title: Māori Cultural Identity and Education

authors: Hawaikirangi-Pere, Charmaine

subjects: Identity

abstract: Underachievement of Māori students in mainstream schools has been a major topic of discussion by politicians and educational researchers in recent years. Research has shown that a secure cultural identity can enhance a person’s overall well-being and furthermore improve their chances of educational success. However, in reality, statistics show that a high percentage of the Māori population have little or no knowledge of their language and culture. The research question in this study will ask Māori whānau how they perceive cultural identity in relation to their children’s education.
Principles of Kaupapa Māori, Takepū and indigenous research and qualitative research methods have been used to ensure that participants were culturally and ethically respected. Participants interviewed in this study are members of my own whānau and some close friends. As an insider researcher I was committed to ensuring that my whānau were treated with respect and dignity throughout the research process. 
The interview data has exposed some unexpected issues specifically relating to their educational experiences and cultural identity. In the context of historical records and education for Māori, the findings of this study suggest that the educational experiences of Māori whānau have been, and continue to be, strongly influenced by government policies enforced before and during the period in which they attended school. All the whānau interviewed acknowledged their ethnic identity as Māori, however, most of them had little or no knowledge and understanding of Te Reo Māori nor had they taken part in cultural practices. Government policies restricted the use of the Māori language, disengaged them from their culture and curriculum provision limited expectations for both males and females. Mixed ethnicity and urbanisation were also identified as factors in the loss of their cultural identity. Data also shows that cultural identity loss has progressed on to future generations and influenced Māori whānau priorities and choice of school. 
The aim of this study is to provide educational policy makers with an in-depth understanding of the perspectives of Māori whānau determine their specific needs in education and propose some suggestions on how to improve achievement of Māori whānau in mainstream schools.

text: Māori Cultural Identity and Education Underachievement of Māori students in mainstream schools has been a major topic of discussion by politicians and educational researchers in recent years. Research has shown that a secure cultural identity can enhance a person’s overall well-being and furthermore improve their chances of educational success. However, in reality, statistics show that a high percentage of the Māori population have little or no knowledge of their language and culture. The research question in this study will ask Māori whānau how they perceive cultural identity in relation to their children’s education.
Principles of Kaupapa Māori, Takepū and indigenous research and qualitative research methods have been used to ensure that participants were culturally and ethically respected. Participants interviewed in this study are members of my own whānau and some close friends. As an insider researcher I was committed to ensuring that my whānau were treated with respect and dignity throughout the research process. 
The interview data has exposed some unexpected issues specifically relating to their educational experiences and cultural identity. In the context of historical records and education for Māori, the findings of this study suggest that the educational experiences of Māori whānau have been, and continue to be, strongly influenced by government policies enforced before and during the period in which they attended school. All the whānau interviewed acknowledged their ethnic identity as Māori, however, most of them had little or no knowledge and understanding of Te Reo Māori nor had they taken part in cultural practices. Government policies restricted the use of the Māori language, disengaged them from their culture and curriculum provision limited expectations for both males and females. Mixed ethnicity and urbanisation were also identified as factors in the loss of their cultural identity. Data also shows that cultural identity loss has progressed on to future generations and influenced Māori whānau priorities and choice of school. 
The aim of this study is to provide educational policy makers with an in-depth understanding of the perspectives of Māori whānau determine their specific needs in education and propose some suggestions on how to improve achievement of Māori whānau in mainstream schools.

year: 2013

title: Occlusion prediction for kiwifruit yield estimation

authors: Seabright, Matthew James

subjects: kiwifruit

abstract: Kiwifruit is very important to the New Zealand economy, bringing in NZ$2.39 billion in the 2017/2018 season and projected to grow to NZ$4.5 billion by 2025. Every season, the expected yield from each orchard is estimated. These estimates are used for both on-orchard decisions regarding thinning and spraying, and industry level decisions regarding export pricing, supply agreements, labour requirements, packaging quantities and more. The current method for yield estimation is manual and prone to errors. In the 2016/17 growing season, green kiwifruit estimates were 5.9% lower than actual harvest yield, resulting in over 5 million trays (approximately 18,000 tons) of fruit being disposed of.

An automated system could reduce errors saving the industry significant amounts of money. Such a system could realise other benefits such as providing more granular information on orchard performance to growers and increasing labour efficiency and crop uniformity via targeted labour. Other automated fruit yield estimation systems have been developed but have suffered from sub-optimal performance due to occlusion of fruit. The work presented here introduces a system that has been developed with the aim of minimising occlusion where possible and employs an occlusion prediction model to account for remaining occlusion. The system utilises stereo vision, a 3D lidar unit, an inertial measurement unit and LED lighting mounted on an all terrain vehicle (ATV).
Data is captured across 16 maturity areas, consisting of 33.9 Ha of commercial kiwifruit orchards. A simultaneous localisation and mapping system is used to locate the ATV within the orchard. A convolutional neural network detects kiwifruit, which are localised via stereo triangulation. Individual fruit are tracked through overlapping images to reduce occlusion while ensuring no double counting. Fruit are counted and an occlusion prediction model is applied to account for the unseen fruit.

The system is able to predict orchard scale fruit yield with a mean absolute percentage error of 0.68%. This error rate was obtained from an independent test dataset and ground truth data obtained from a commercial kiwifruit packhouse. The system can also generate visualisations of orchards showing all individual detected fruit in 3D, fruit density maps and canopy density maps. The ability of the system to predict yield with high accuracy and at orchard scale sets it apart from previous work. It is also the largest scale study currently known, consisting of over 15 million fruit.

text: Occlusion prediction for kiwifruit yield estimation Kiwifruit is very important to the New Zealand economy, bringing in NZ$2.39 billion in the 2017/2018 season and projected to grow to NZ$4.5 billion by 2025. Every season, the expected yield from each orchard is estimated. These estimates are used for both on-orchard decisions regarding thinning and spraying, and industry level decisions regarding export pricing, supply agreements, labour requirements, packaging quantities and more. The current method for yield estimation is manual and prone to errors. In the 2016/17 growing season, green kiwifruit estimates were 5.9% lower than actual harvest yield, resulting in over 5 million trays (approximately 18,000 tons) of fruit being disposed of.

An automated system could reduce errors saving the industry significant amounts of money. Such a system could realise other benefits such as providing more granular information on orchard performance to growers and increasing labour efficiency and crop uniformity via targeted labour. Other automated fruit yield estimation systems have been developed but have suffered from sub-optimal performance due to occlusion of fruit. The work presented here introduces a system that has been developed with the aim of minimising occlusion where possible and employs an occlusion prediction model to account for remaining occlusion. The system utilises stereo vision, a 3D lidar unit, an inertial measurement unit and LED lighting mounted on an all terrain vehicle (ATV).
Data is captured across 16 maturity areas, consisting of 33.9 Ha of commercial kiwifruit orchards. A simultaneous localisation and mapping system is used to locate the ATV within the orchard. A convolutional neural network detects kiwifruit, which are localised via stereo triangulation. Individual fruit are tracked through overlapping images to reduce occlusion while ensuring no double counting. Fruit are counted and an occlusion prediction model is applied to account for the unseen fruit.

The system is able to predict orchard scale fruit yield with a mean absolute percentage error of 0.68%. This error rate was obtained from an independent test dataset and ground truth data obtained from a commercial kiwifruit packhouse. The system can also generate visualisations of orchards showing all individual detected fruit in 3D, fruit density maps and canopy density maps. The ability of the system to predict yield with high accuracy and at orchard scale sets it apart from previous work. It is also the largest scale study currently known, consisting of over 15 million fruit.

year: 2020