title: A Mātauranga Māori Perspective of Literacy for Adult Learners

authors: Furness, Jane Amanda

abstract: Globally, literacy can be conceived of in different ways. Two perspectives that have influenced adult literacy policy internationally are the economic functionalist and the sociocultural. In Aotearoa New Zealand, Māori educators have repeatedly advanced a mātauranga Māori perspective of literacy. This perspective has parallels with the embodied, practice-based multiliteracies and sociomateriality of the sociocultural perspective but less so with the dominant functionalist perspective. To address how Māori views have been side-lined in adult literacy policy development, we seek to clarify this view and foreground Māori-led policy recommendations that date back to the creation of the New Zealand Adult Literacy Strategy in 2001. We also highlight the relevance of this perspective by sharing the success and effectiveness of Māori-led adult literacy programmes. In doing so, we demonstrate the need for a biliteracy approach to adult literacy policy to reflect our bicultural nation and ensure Māori aspirations for literacy are met.

text: A Mātauranga Māori Perspective of Literacy for Adult Learners Globally, literacy can be conceived of in different ways. Two perspectives that have influenced adult literacy policy internationally are the economic functionalist and the sociocultural. In Aotearoa New Zealand, Māori educators have repeatedly advanced a mātauranga Māori perspective of literacy. This perspective has parallels with the embodied, practice-based multiliteracies and sociomateriality of the sociocultural perspective but less so with the dominant functionalist perspective. To address how Māori views have been side-lined in adult literacy policy development, we seek to clarify this view and foreground Māori-led policy recommendations that date back to the creation of the New Zealand Adult Literacy Strategy in 2001. We also highlight the relevance of this perspective by sharing the success and effectiveness of Māori-led adult literacy programmes. In doing so, we demonstrate the need for a biliteracy approach to adult literacy policy to reflect our bicultural nation and ensure Māori aspirations for literacy are met.

year: 2023-10-23

title: "Takahi ngā takahanga o ngā tūpuna" - Tramp the pathways of our ancestors

authors: Williams, Taniwha

subjects: Māori health and wellbeing

abstract: The rise of reconnecting to holistic approaches to health to improve wellbeing outcomes for Māori has become increasingly prominent in recent years. Such developments have highlighted the need to introduce traditional Māori concepts, values and practices within whānau, hapū and iwi as vehicles for promoting and improving Māori health. This research had two objectives. Firstly, it aimed to explore the process of reclaiming mātauranga Māori (Māori knowledge systems) with my whānau who had limited access to te ao Māori (the Māori world). The second objective sought to explore the experiences of my whānau reconnecting with te reo me ōna tikanga (Māori language and culture). Using the Whiti Te Rā as a guide informed the design and structure of the wānanga (workshops). The Whiti Te Rā is a therapeutic model designed to improve health and wellbeing outcomes for Māori by developing and enhancing a cultural identity. Central to this model are six Māori customary practices and values that provide pathways to wellbeing and flourishing mauri. These dimensions also have synergies with other models of health – Te Whare Tapa Whā, Te Wheke. Four tāne (men) from my whānau took part in this research. We used the Pūrākau Method to record, explore, and analyse the narratives that emerged following each wānanga. The key findings from this research included connection to history, whakapapa and wairua; connection to pepeha and cultural practices; connection to self as a Māori; connection through whanaungatanga; and connection to taiao (the environment). This study showed that Māori models of health and wellbeing are consistent in demonstrating their effectiveness in connecting Māori to their language and culture. Despite the impact of colonisation, reconnection to customary practices and values was meaningful and valuable to my whānau. Future research is needed to revitalise, regenerate and reclaim a thriving Māori identity.

text: "Takahi ngā takahanga o ngā tūpuna" - Tramp the pathways of our ancestors The rise of reconnecting to holistic approaches to health to improve wellbeing outcomes for Māori has become increasingly prominent in recent years. Such developments have highlighted the need to introduce traditional Māori concepts, values and practices within whānau, hapū and iwi as vehicles for promoting and improving Māori health. This research had two objectives. Firstly, it aimed to explore the process of reclaiming mātauranga Māori (Māori knowledge systems) with my whānau who had limited access to te ao Māori (the Māori world). The second objective sought to explore the experiences of my whānau reconnecting with te reo me ōna tikanga (Māori language and culture). Using the Whiti Te Rā as a guide informed the design and structure of the wānanga (workshops). The Whiti Te Rā is a therapeutic model designed to improve health and wellbeing outcomes for Māori by developing and enhancing a cultural identity. Central to this model are six Māori customary practices and values that provide pathways to wellbeing and flourishing mauri. These dimensions also have synergies with other models of health – Te Whare Tapa Whā, Te Wheke. Four tāne (men) from my whānau took part in this research. We used the Pūrākau Method to record, explore, and analyse the narratives that emerged following each wānanga. The key findings from this research included connection to history, whakapapa and wairua; connection to pepeha and cultural practices; connection to self as a Māori; connection through whanaungatanga; and connection to taiao (the environment). This study showed that Māori models of health and wellbeing are consistent in demonstrating their effectiveness in connecting Māori to their language and culture. Despite the impact of colonisation, reconnection to customary practices and values was meaningful and valuable to my whānau. Future research is needed to revitalise, regenerate and reclaim a thriving Māori identity.

year: 2024

title: Experiments with multi-view multi-instance learning for supervised image classification

authors: Mayo, Michael

subjects: computer science

abstract: In this paper we empirically investigate the benefits of multi-view multi-instance (MVMI) learning for supervised image classification. In multi-instance learning, examples for learning contain bags of feature vectors and thus data from different views cannot simply be concatenated as in the single-instance case. Hence, multi-view learning, where one classifier is built per view, is particularly attractive when applying multi-instance learning to image classification. We take several diverse image data sets—ranging from person detection to astronomical object classification to species recognition—and derive a set of multiple instance views from each of them. We then show via an extensive set of 10_10 stratified cross-validation experiments that MVMI, based on averaging predicted confidence scores, generally exceeds the performance of traditional single-view multi-instance learning, when using support vector machines and boosting as the underlying learning algorithms.

text: Experiments with multi-view multi-instance learning for supervised image classification In this paper we empirically investigate the benefits of multi-view multi-instance (MVMI) learning for supervised image classification. In multi-instance learning, examples for learning contain bags of feature vectors and thus data from different views cannot simply be concatenated as in the single-instance case. Hence, multi-view learning, where one classifier is built per view, is particularly attractive when applying multi-instance learning to image classification. We take several diverse image data sets—ranging from person detection to astronomical object classification to species recognition—and derive a set of multiple instance views from each of them. We then show via an extensive set of 10_10 stratified cross-validation experiments that MVMI, based on averaging predicted confidence scores, generally exceeds the performance of traditional single-view multi-instance learning, when using support vector machines and boosting as the underlying learning algorithms.

year: 2011