Imagined, prescribed and actual text trajectories: the ‘problem’ with case notes in contemporary social work

Drawing on a text-oriented action research ethnography of the writing practices of UK-based social workers, this paper focuses on a key but problematic aspect of everyday, professional textual practice – the production of “case notes.” Using data drawn from interviews, workshops, texts and observation, the paper locates case notes within social work everyday practice and explores the entextualization of three distinct case notes. The heuristic of imagined, prescribed and actual trajectories is used to track specific instances of entextualization and to illustrate why the production of case notes is a particularly complex activity. A key argument is that in the institutional imaginary, and reflected in the institutionally prescribed trajectory, case notes are construed as a comprehensive record of all actions, events and interactions, prior to and providing warrants for all other documentation. However, they are in actual practice produced as parts of clusters of a range of different text types which, together, provide accounts of, and for, actions and decisions. This finding explains why case notes are often viewed as incomplete and raises fundamental questions about how they should be evaluated. The complexity of case notes as an everyday professional practice is underscored in relation to professional voice, addressivity and textual temporality

Reductive homogeneous spaces and nonassociative algebras

The purpose of these survey notes is to give a presentation of a classical theorem of Nomizu that relates the invariant affine connections on reductive homogeneous spaces and nonassociative algebras.Comment: 28 pages. The first version constituted the notes of a course given at the CIMPA research school "G\'eom\'etrie diff\'erentielle et alg\`ebres non associatives", held in Marrakech, April 13-24, 201

Towards Automatic Generation of Shareable Synthetic Clinical Notes Using Neural Language Models

Large-scale clinical data is invaluable to driving many computational scientific advances today. However, understandable concerns regarding patient privacy hinder the open dissemination of such data and give rise to suboptimal siloed research. De-identification methods attempt to address these concerns but were shown to be susceptible to adversarial attacks. In this work, we focus on the vast amounts of unstructured natural language data stored in clinical notes and propose to automatically generate synthetic clinical notes that are more amenable to sharing using generative models trained on real de-identified records. To evaluate the merit of such notes, we measure both their privacy preservation properties as well as utility in training clinical NLP models. Experiments using neural language models yield notes whose utility is close to that of the real ones in some clinical NLP tasks, yet leave ample room for future improvements.Comment: Clinical NLP Workshop 201

An Overview of LISA Data Analysis Algorithms

The development of search algorithms for gravitational wave sources in the LISA data stream is currently a very active area of research. It has become clear that not only does difficulty lie in searching for the individual sources, but in the case of galactic binaries, evaluating the fidelity of resolved sources also turns out to be a major challenge in itself. In this article we review the current status of developed algorithms for galactic binary, non-spinning supermassive black hole binary and extreme mass ratio inspiral sources. While covering the vast majority of algorithms, we will highlight those that represent the state of the art in terms of speed and accuracy.Comment: 21 pages. Invited highlight article appearing in issue 01 of Gravitational Waves Notes, "GW Notes", edited by Pau Amaro-Seoane and Bernard F. Schutz at: http://brownbag.lisascience.org/lisa-gw-notes