108 research outputs found

    Dynamic discrete-time duration models. (REVISED)

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    Discrete-time grouped duration data, with one or multiple types of terminating events, are often observed in social sciences or economics. In this paper we suggest and discuss dynamic models for flexible Bayesian nonparametric analysis of such data. These models allow simultaneous incorporation and estimation of baseline hazards and time-varying covariate effects, without imposing particular parametric forms. Methods for exploring the possibility of time-varying effects, as for example the impact of nationality or unemployment insurance benefits on the probability of re-employment, have recently gained increasing interest. Our modelling and estimation approach is fully Bayesian and makes use of Markov Chain Monte Carlo (MCMC) simulation techniques. A detailed analysis of unemployment duration data, with full-time job, part-time job and other causes as terminating events, illustrates our methods and shows how they can be used to obtain refined results and interpretations

    Dynamic and semiparametric models

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    This paper surveys dynamic or state space models and their relationship to non- and semiparametric models that are based on the roughness penalty approach. We focus on recent advances in dynamic modelling of non-Gaussian, in particular discrete-valued, time series and longitudinal data, make the close correspondence to semiparametric smoothing methods evident, and show how ideas from dynamic models can be adopted for Bayesian semiparametric inference in generalized additive and varying coefficient models. Basic tools for corresponding inference techniques are penalized likelihood estimation, Kalman filtering and smoothing and Markov chain Monte Carlo (MCMC) simulation. Similarities, relative merits, advantages and disadvantages of these methods are illustrated through several applications

    Ueber eine bequeme Methode zur Darstellung des Acetonylacetons

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    Spectroscopic Evidence for Clusters of Like-Charged Ions in Ionic Liquids Stabilized by Cooperative Hydrogen Bonding

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    Infrared spectroscopy and density functional theory calculations provide strong evidence for the formation of clusters of like-charged ions in ionic liquids. With decreasing temperature, cooperative hydrogen bonding overcomes repulsive electrostatic interaction. The resulting cyclic tetramers nicely resemble well-known molecular clusters of alcohols

    Zooming in and out : studying practices by switching theoretical lenses and trailing connections

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    This paper contributes to re-specifying a number of the phenomena of interest to organisational studies in terms of patterns of socio-material practices and their effects. It does so by outlining a vocabulary and strategy that make up a framework for theorising work and organisational practices. The vocabulary is based on number of sensitising concepts that connote practice as an open-ended, heterogeneous accomplishment which takes place within a specific horizon of sense and a set of concerns which the practice itself brings to bear. The strategy is based on the metaphorical movement of "zooming in" and "zooming out of" practice. The zooming in and out are obtained through switching theoretical lenses and repositioning in the field, so that certain aspects of the practice are fore-grounded while others are bracketed. Building on the results of an extended study of telemedicine, the paper discusses in detail the different elements of the framework and how it enhances our capacity to re-present practice. The paper concludes with some considerations on how the proposed approach can assist us in advancing the research agenda of organizational and work studies

    Algorithms, governance, and governmentality:on governing academic writing

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    Algorithms, or rather algorithmic actions, are seen as problematic because they are inscrutable, automatic, and subsumed in the flow of daily practices. Yet, they are also seen to be playing an important role in organizing opportunities, enacting certain categories, and doing what David Lyon calls ‘‘social sorting.’’ Thus, there is a general concern that this increasingly prevalent mode of ordering and organizing should be governed more explicitly. Some have argued for more transparency and openness, others have argued for more democratic or value-centered design of such actors. In this article, we argue that governing practices—of, and through algorithmic actors—are best understood in terms of what Foucault calls governmentality. Governmentality allows us to consider the performative nature of these governing practices. They allow us to show how practice becomes problematized, how calculative practices are enacted as technologies of governance, how such calculative practices produce domains of knowledge and expertise, and finally, how such domains of knowledge become internalized in order to enact self-governing subjects. In other words, it allows us to show the mutually constitutive nature of problems, domains of knowledge, and subjectivities enacted through governing practices. In order to demonstrate this, we present attempts to govern academic writing with a specific focus on the algorithmic action of Turnitin
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