A construction method is given for all factors that satisfy the assumptions of the model for factor analysis, including partially determined factors where certain error variances are zero. Various criteria for the seriousness of indeterminacy are related. It is shown that B. F. Green's (1976) conjecture holds: For a linear factor predictor the mean squared error of prediction is constant over all possible factors. A simple and general geometric interpretation of factor indeterminacy is given on the basis of the distance between multiple factors. It is illustrated that variable elimination can have a large effect on the seriousness of factor indeterminacy. A simulation study reveals that if the mean square error of factor prediction equals .5, then two thirds of the persons are "correctly" selected by the best linear factor predictor. (PsycINFO Database Record (c) 2009 APA, all rights reserved)
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We share insights from our practice-based experimentation with ‘feral’ ways of sensemaking in the context of creative transformational practices. Drawing on three art and design research projects, we discuss how feral ways–open-ended, spontaneous, welcoming indeterminacy – may foster more-than-human co-creation of knowledge and data, and nurture shifts from anthropocentric ‘making sense of’ to relational ‘making sense-with’ other-than-human creatures. Through our cases, we illustrate how experimenting with feralness can foreground issues of power, agency, and control in the currently human-centric discourses around data, technology, and sensemaking in eco-social transformation. Our insights may nurture critical more-than-human perspectives in creative eco-social inquiries.
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The subject of factor indeterminacy has a vast history in factor analysis (Guttman, 1955; Lederman, 1938; Wilson, 1928). It has lead to strong differences in opinion (Steiger, 1979). The current paper gives necessary and sufficient conditions for observability of factors in terms of the parameter matrices and a finite number of variables. Five conditions are given which rigorously define indeterminacy. It is shown that (un)observable factors are (in)determinate. Specifically, the indeterminacy proof by Guttman is extended to Heywood cases. The results are illustrated by two examples and implications for indeterminacy are discussed.
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Gesprek over esthetiek en organisaties waarbij gereflecteerd wordt op de muziek van John Cage.
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Sufficient conditions for mean square convergence of factor predictors in common factor analysis are given by Guttman, by Williams, and by Schneeweiss and Mathes. These conditions do not hold for confirmatory factor analysis or when an error variance equals zero (Heywood cases). Two sufficient conditions are given for the three basic factor predictors and a predictor from rotated principal components analysis to converge to the factors of the model for confirmatory factor analysis, including Heywood cases. For certain model specifications the conditions are necessary. The conditions are sufficient for the existence of a unique true factor. A geometric interpretation is given for factor indeterminacy and mean square convergence of best linear factor prediction.
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Historian Yuval Harari writes in his 21 Lessons for the 21st Century that due to increasing automation and robotization, large groups of people will probably become completely redundant in the labour market in the near future. He proposes a basic income as a solution. In this article it is argued that it may be a solution to fight poverty, but in itself it doesn’t provide meaningful connectedness, which is an important result of labour.
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Friction in the classroom may create useful tension for teachers when they attempt to discuss sensitive topics as part of democratic learning. Due to the openness and indeterminacy of these topics, students can experience what it is like to be (political) subjects in a diverse society and become aware of other people’s subjectness in a charged classroom. To better understand how to handle educational friction in the classroom, we observed and interviewed nine Dutch expert teachers and analyzed the empirical data by using our Educational Friction Modelling Framework as a heuristic lens. This study shows how teachers allowed extreme statements and used the subsequent friction during their lessons, challenged and provoked their students, made room for their pupils in several ways to enhance their participation, and made a distinction between rationality and emotions in the classroom. We argue that our framework sheds light on what charges the classroom and contributes to the further development of contained risk-taking as part of democratic education.
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The assumptions of the model for factor analysis do not exclude a class of indeterminate covariances between factors and error variables (Grayson, 2003). The construction of all factors of the model for factor analysis is generalized to incorporate indeterminate factor-error covariances. A necessary and sufficient condition is given for indeterminate factor-error covariances to be arbitrarily small, for mean square convergence of the regression predictor of factor scores, and for the existence of a unique determinate factor and error variable. The determinate factor and error variable are uncorrelated and satisfy the defining assumptions of factor analysis. Several examples are given to illustrate the results.
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The level of work engagement is an important aspect of organizational culture. In this empirical study the relation between engagement and experienced professionalism of probation officers is investigated. Starting from ideal-typical theories on professionalism, a psychometric instrument for measuring experienced professionalism was developed and administered to a sample of Dutch probation officers. Two reliable scales could be constructed that account for 64% of the variance in work engagement. Of these, professional ethos (humanistic values) is the most important predictor of work engagement in probation. Professional facilitation (support from the surroundings), however, also contributes to engagement.
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This paper introduces the Feral Map, an open online map that brings together different creative practices questioning the dominant extractive, technocentric rendering and legitimising of particular algorithmic futures. Building on its initial development drawn upon open urban tree data, it invites people to explore and engage with their surroundings in creative, unfamiliar ways and share their experiences in the form of stories, using different kinds of media, sensory impressions, and personal expressions. These stories can be offered to existing places and local “creatures” (such as animals, ambiences, and glitches) or become new creatures on their own, emphasising mattering and entanglements: that change is the only constant in life. Through this, the map obscures the currently available–mostly quantitative–data about a place, and can help to raise questions about power, values, and structural inequalities that shape the place and its future. The Feral Map has been evolving to include such stories and creatures–or messy data–from different creative, practice-based research projects. Our paper presents the theoretical framing of the Feral Map and its design, how it has been transforming along with the involved projects, as well as our learnings from the process and possible future directions.
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