Indigenous Statistics: From Data Deficits to Data Sovereignty by Chris Andersen, Maggie Walter, Tahu Kukutai
English | February 27, 2025 | ISBN: 1032002506 | 166 pages | EPUB | 1.12 Mb
This second edition of the groundbreaking Indigenous Statistics opens up a major new approach to research across the disciplines and applied fields. While qualitative methods have been rigorously critiqued and reformulated, the population statistics relied on by virtually all research on Indigenous Peoples continue to be taken for granted as straightforward, transparent numbers. Drawing on a diverse new author team, this book dismantles that persistent positivism with a forceful critique, then fills the void with a new paradigm for Indigenous quantitative methods using concrete examples of research projects from first world Indigenous Peoples in the United States, Australia, Aotearoa New Zealand and Canada. Concise and accessible, it is an ideal supplementary text as well as a core component of the methodological toolkit for anyone conducting Indigenous research or using Indigenous population statistics. This is an essential text for students studying quantitative methods, statistics and research methods.
The Open Access version of this book, available athttp://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non-Commercial-No Derivative Licence (CC-BY-NC-ND) 4.0 license.
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resents a conceptual framework to measure the readiness of adopting Industry 4.0 in advanced manufacturing systems.Discusses the impact of smart manufacturing on sustainable development and integration of Industry 4.0 and additive manufacturing.Covers topics such as intelligent automation systems, machine learning-based preventive maintenance, and the Internet of Things-enabled additive manufacturing in Industry 4.0.Explains cyber-physical system integration with Industry 4.0 technologies, cyber-physical systems in industrial robotics, and green cyber-physical systems.Illustrates optimization of process parameters using fuzzy-based multi-criteria decision-making tools and life cycle assessment models in Industry 4.0.This book is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of industrial engineering, production engineering, mechanical engineering, supply chain management, and manufacturing engineering.
