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This book examines the relationships between educational policy, space and place. With urbanisation as one of the central concerns for the future, relationships between the city, educational policy, and social and educational inequality deserve sustained examination. Gulson's book is a rich and needed contribution to these areas of study

AbstractAutomated decision-making is a process in which an algorithm collects and analyses data, derives information, applies this information, and recommends an action, at times using forms of Artificial Intelligence (Richardson 2021). This paper proposes that we need to locate automated decision-making as part of the history of educational policy and governance, as well as increasingly networked cultural records or digital archives. As such, we explore the history and present of automated decision systems across a range of cultural records spanning several categories: data, algorithm, and AI-based technologies; innovation and industry; philanthropy and funding; policy and legislation; spatiality and socioeconomics; plus, activism, and communities. To do so, we created an interdisciplinary archival heuristic as a research tool to retrace these interrelated cultural records shaping data infrastructure and inequalities. We then tested this tool in the context of the school admission matching algorithm in New York City. Our central aim is to help counter discourses about the newness and efficiencies of introducing automation and algorithms across education reform initiatives. The education counter-archiving heuristic introduced therefore offers a novel research tool to explore the intersecting history, present, and future of automated decision-making systems, such as school choice algorithms.

Education policy is premised on its instrumentalist approach. This instrumentalism is based on narrow assumptions concerning people (the subject), decision-making (power), problem-solving (science and methodology), and knowledge (epistemology). Policy, Geophilosophy and Education reconceptualises the object , and hence, the objectives, of education policy. Specifically, the book illustrates how education policy positions and constitutes objects and subjects through emergent policy arrangements that simultaneously influence how policy is sensed, embodied, and enacted. The book examines the disciplinary and multi-disciplinary approaches to education policy analysis over the last sixty years, and reveals how policy analysis constitutes the ontologies and epistemologies of policy. In order to reconceptualise policy, Policy, Geophilosophy and Education uses ideas of spatiality, affect and problematization from the disciplines of geography and philosophy. The book problematizes case-vignettes to illustrate the complex and often paradoxical relations between neo-liberal education policy equity, and educational inequalities produced in the representational registers of race and ethnicity

AbstractThe potential of applying a 'technical democracy' (Callon et al. 2009) to the context of sociotechnical controversies in education is the focus of this paper. This process reflects an emergent 'thought collective' (Fleck 1979) whose common interests, yet diverse expertise, are articulated through provisional objects and infrastructure for collective and experimental knowledge production. The technique of 'prototyping' was then deployed for a design experiment to: first, slow down, or suspend, existing power relations of co-evolving technologies and methodologies and, second, to accelerate, or expand, new possibilities and configurations for democratisation. Education prototyping is then introduced, with the intent to co-produce pluralistic spaces that expose challenges and test possibilities. Key aspects include the following: (i) prototyping dynamics: problematization and prefiguration; and, (ii) prototyping practices: spanning the temporal, methodological, relational, material, and spatial. These aspects were tested in the context of a research project exploring automated essay scoring in Australian schools. While always situated and partial, we argue that prototyping offers a unique device to interrupt and experiment with the politics of collaboratively researching increasingly networked and commercialised technologies across education and society.

Cover -- Title -- Copyright -- CONTENTS -- Notes on contributors -- Acknowledgements -- Introduction: theory, policy, methodology -- PART I Theorists -- 1 Bourdieu and doing policy sociology in education -- 2 Michel de Certeau, everyday life and cultural policy studies in education -- 3 Repeating Deleuze and Guattari: towards a politics of method in education policy studies -- 4 Derrida: the 'impossibility' of deconstructing educational policy enactment -- 5 Education policies as discursive formations: a Foucauldian optic -- 6 Lacanian perspectives on education policy analysis -- PART II Concepts and theories -- 7 Situated, relational and practice-oriented: the actor-network theory approach -- 8 Thinking educational policy and management through (frictional) concepts of affects -- 9 Assemblage theory and education policy sociology -- 10 Counterpublics, crisis and critique: a feminist socio-historical approach to researching policy -- 11 Embodying policy studies: feminist genealogy as methodology -- 12 Governmentality: Foucault's concept for our modern political reasoning -- 13 Taking a 'material turn' in education policy research? -- 14 Mobilities paradigm and policy research in education -- 15 A narrative approach to policy analysis -- 16 Queer theory, policy and education -- 17 Thinking rhizomatically: using Deleuze in education policy contexts -- 18 Relational space and education policy analysis -- Index.

This article examines the history of a similarity measure—the Mahalanobis Distance Function—and its movement from colonial India into contemporary artificial intelligence technologies, including facial recognition, and its reapplication into postcolonial India. The article identifies how the creation of the Distance Function was connected to the colonial "problem" of caste and ethnic classification for British bureaucracy in 1920-1930s India. This article demonstrates that the Distance Function is a statistical method, originating to make anthropometric caste distinctions in India, that became both a technical standard and a mobile racialized technique, utilized in machine learning applications. The creation of the Distance Function as a measure of "similitude" at a particular period of colonial state-making helped to model wider categories of classification which have proliferated in facial recognition technology. Overall, we highlight how a measurement function that operates in recognition technologies today can be traced across time and space to other racialized contexts.