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Titlebook: Indigenous Children Growing Up Strong; A Longitudinal Study Maggie Walter,Karen L. Martin,Gawaian Bodkin-Andre Book 2017 The Editor(s) (if

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书目名称Indigenous Children Growing Up Strong
副标题A Longitudinal Study
编辑Maggie Walter,Karen L. Martin,Gawaian Bodkin-Andre
视频video
概述Uses longitudinal study data and includes perspectives from the Aboriginal community.Addresses a range of issues including race, technology, education, health and well-being.Concludes with policy impl
图书封面Titlebook: Indigenous Children Growing Up Strong; A Longitudinal Study Maggie Walter,Karen L. Martin,Gawaian Bodkin-Andre Book 2017 The Editor(s) (if
描述.This edited collection by leading Australian Aboriginal scholars uses data from the Longitudinal Study of Indigenous Children (LSIC) to explore how Aboriginal and Torres Strait Islander children are growing up in contemporary Australia. The authors provide an overview of the study, including the Indigenous methodological and ethical framework which guides the analysis. They also address the resulting policy ramifications, alongside the cultural, social, educational and family dynamics of Indigenous children’s lives.. . . .Indigenous Children Growing Up Strong. will be of interest to students and scholars in the areas of sociology, social work, anthropology and childhood and youth studies..
出版日期Book 2017
关键词aboriginal; Australia; youth; sociology; school; education; bullying; society; identity; health; policy
版次1
doihttps://doi.org/10.1057/978-1-137-53435-4
isbn_ebook978-1-137-53435-4
copyrightThe Editor(s) (if applicable) and The Author(s) 2017
The information of publication is updating

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Maggie Walter,Karen L. Martin,Gawaian Bodkin-Andrewsque words covered by a model varies from few to several times depending on which model vocabulary is taken as reference. The transformed word representations are also well correlated (average correlation up to 0.801 for words in Simlex-999 dataset) with the native target model representations indica
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Maggie Walter,Mick Dodson,Sharon Barnesque words covered by a model varies from few to several times depending on which model vocabulary is taken as reference. The transformed word representations are also well correlated (average correlation up to 0.801 for words in Simlex-999 dataset) with the native target model representations indica
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Terry Dunbar,Margaret Scrimgeouris statistically significant. We also perform an analysis of the variation in topic between the two epochs, to compare with the variation at the style level. These analyses show that texts from the two periods can indeed be distinguished, both from the point of view of style and from that of semanti
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Karen L. Martinh texts using unsupervised cluster analysis and supervised machine learning..The results of our study show that the Fiqh schools have distinctive text style features that can be used to indicate authorship. The observations from the cluster analysis experiment using a number of different distance me
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Terry Dunbar,Margaret Scrimgeouris statistically significant. We also perform an analysis of the variation in topic between the two epochs, to compare with the variation at the style level. These analyses show that texts from the two periods can indeed be distinguished, both from the point of view of style and from that of semanti
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