Negotiating professional knowledge and responsibility in cross-sectoral Telemedicine

In ongoing efforts of rationalization and retrenchment in the Danish health care sector, tasks are increasingly moved from costly specialized hospital departments to the primary health care sec- tor, where less specialized personnel take on these tasks. Telemedicine plays an important role in facilitating local access to specialized competences at central hospitals through ICT systems and establishes new virtual spaces for cross-sectoral cooperation between hospital and municipal health care workers. In an explorative ethnographic study, comprising interviews and participant observation, of telemedicine-based interaction between community nurses and specialized hospi- tal nurses, we show how the ‘tele-ulcer’ system becomes a site for professional development for community nurses, although a hierarchization of professional knowledge also takes place. Further- more, extensive articulation work is necessary to make the tele-ulcer system work.We illuminate how contradictory divisions of responsibility may result from the design of the sociotechnical sys- tem, leaving professionals to deal with risks and insecurity

Small business survey: linking 2006 and 2007 waves to the IDBR

This report describes work to link two waves of the Small Business Survey (SBS) to the Inter-Departmental Business Register (IDBR)1. The first is the Annual Small Business Survey 2006/07, hereafter SBS 2006; the second is the survey for 2007/8, hereafter SBS 2007. The linking work has been undertaken by Belmana and Middlesex University; IFF Research conducted both surveys and has overseen this work. The focus of this research was to understand the strengths and weaknesses of different methods of linking and then develop an approach for application to the 2006 and 2007 waves of the survey. A particular difficulty, as older waves of SBS are linked to the IDBR, is the changes to businesses that would have occurred since the survey. This work has taken steps to reduce the effect of the age of the survey on the quality of the data linking, by linking to historic vintages of the IDBR and the Companies House register. The report also reviews earlier work by the Office for National Statistics (ONS) linking the 2010 and 2012 SBS surveys to the IDBR. The project draws on insights from this, but introduces new linking methods that improve link rates. Various quality checks have been undertaken and, given the surveys were conducted almost a decade ago, the ability to link a higher proportion of respondents to the IDBR than achieved for the 2010 survey indicates the linking of SBS can be undertaken even for relatively old waves. Some preliminary analysis of the linked survey data suggests that there is potential for understanding the more long-term outcomes for businesses and correlating these with SBS responses

Hard-working heroes or curious students?:Au pair positioning, organizing and negotiation

The precarious position and poor working conditions of au pairs in the Nordic and other western labor markets are well documented. Furthermore, research on au pairs and migrant domestic workers emphasizes many obstacles to their organizing (e.g., in trade unions) and negotiation to improve their working conditions. Using an ethnographic study of Filipino au pairs in Denmark as an illustrative case, we supplement this previous research by presenting an analytical approach inspired by governmentality studies. This approach highlights the complex transnational interplay of migration policies and practices affecting Filipino au pairs’ positioning in the Danish labor market and contributes to exploring how this positioning relates to their prospects for negotiating and organizing. We suggest that with a close examination of the often contradictory and multifaceted positioning of migrant workers in transnational policy fields, not only obstacles but also possibilities for negotiation and organizing to improve working conditions will become visibl

Transforming bodywork in eldercare with wash-and-dry toilets

This paper addresses how the introduction of welfare technologies in Denmark makes the body- work of eldercare an object of public governance, and investigates how wash-and-dry toilets co-constitute professional care work. First, a theoretical frame is established for studying care, with an emphasis on bodywork as a sociomaterial and collective accomplishment. The paper then unfolds the great expectations tied to welfare technologies in general, and wash-and-dry toilets specifically. Turning to differentiated examples of situated uses of the toilets, the complexity of making the toilets work within the context of professional eldercare is illustrated. Some of the uses of the toilets in care work are in concordance with policy expectations. Other uses demonstrate difficulties in satisfying the great expectations and call for a more complex understanding of what it takes to achieve dignified, technologically assisted care without silencing the skills and profes- sionalism of care workers

Kaggle forecasting competitions: An overlooked learning opportunity

Competitions play an invaluable role in the field of forecasting, as exemplified through the recent M4 competition. The competition received attention from both academics and practitioners and sparked discussions around the representativeness of the data for business forecasting. Several competitions featuring real-life business forecasting tasks on the Kaggle platform has, however, been largely ignored by the academic community. We believe the learnings from these competitions have much to offer to the forecasting community and provide a review of the results from six Kaggle competitions. We find that most of the Kaggle datasets are characterized by higher intermittence and entropy than the M-competitions and that global ensemble models tend to outperform local single models. Furthermore, we find the strong performance of gradient boosted decision trees, increasing success of neural networks for forecasting, and a variety of techniques for adapting machine learning models to the forecasting task