Reports of Conferences,Institutes, and Seminars

Abstract

This column covers several conference sessions from the 14th annual Electronic Resources & Libraries Conference, providing guidance on how to navigate ebook duplication, improving documentation and workflows, implementing OpenAthens, and experiences with Project SILLVR (Streaming Interlibrary Loan Video Resources)and knowledge bases and related tools (KBART) automation. There is also a report from IFLA’s SIG Library Publishing Mid-Term meeting, which was an ideological meeting in nature, discussing community building, resource sharing, and status updates. A report from the 2018 Charleston Conference is also included.     

Reviews

Abstract

Trina Boukin Nolen reviews Dancing with Digital Natives, Stephanie Rosenblatt reviews The Embedded Librarian and Sarah D. Tusa reviews Collection Development in the Digital Age.     

Ecological inference in the social sciences

Ecological inference is a problem of partial identification, and therefore precise conclusions are rarely possible without the collection of individual level (identifying) data. Without such data, sensitivity analyses provide the only recourse. In this paper we review and critique recent approaches to ecological inference in the social sciences, and describe in detail hierarchical models, which allow both sensitivity analysis and the incorporation of individual level data into an ecological analysis. A crucial element of a sensitivity analysis in such models is prior specification, and we detail how this may be carried out. Furthermore, we demonstrate how the inclusion of a small amount of individual level data from a small number of ecological areas can dramatically improve the properties of such estimates.     

Alleviating linear ecological bias and optimal design with subsample data

Summary.  We illustrate that combining ecological data with subsample data in situations in which a linear model is appropriate provides two main benefits. First, by including the individual level subsample data, the biases that are associated with linear ecological inference can be eliminated. Second, available ecological data can be used to design optimal subsampling schemes that maximize information about parameters. We present an application of this methodology to the classic problem of estimating the effect of a college degree on wages, showing that small, optimally chosen subsamples can be combined with ecological data to generate precise estimates relative to a simple random subsample.     

Prevalence of Adult Problem and Pathological Gambling between 2000 and 2005: An Update

Background Excessive gambling is a prominent Public Health problem with high prevalence rates in many countries. Substance abuse and other co-morbidities often constitute a major health hazard for the person which gambles with a loss of material and social resources, as well as being a major concern for his or her significant others. The present study updates and extends prevalence data to include work published between 2000 and 2005 in English and other European languages. Methods In a three-step search and exclusion process, studies with current adult prevalence rates were gathered. Results Almost all studies fulfil basic research standards. The weighted mean prevalence rates for excessive gambling (problem and pathological) are 3.0% for the South Oaks Gambling Survey (problem 1.2%; pathological 1.8%), 3.3% for the Canadian Problem Gambling Index (problem 2.4%; pathological 0.8%) and 3.1% for the DSM-IV (problem 1.9%; pathological 1.2%). Conclusion The prevalence rates are comparable and relatively stable between countries and across survey instruments, and do not differ from earlier reviews. The regular epidemiological monitoring of excessive gambling remains a major Public Health issue although the distinction between pathological and problem gambling is not appropriate for epidemiological research. Further studies are needed with respect to concomitant lifestyle characteristics.     

Toward Disaster‐Resilient Cities: Characterizing Resilience of Infrastructure Systems with Expert Judgments

Resilient infrastructure systems are essential for cities to withstand and rapidly recover from natural and human‐induced disasters, yet electric power, transportation, and other infrastructures are highly vulnerable and interdependent. New approaches for characterizing the resilience of sets of infrastructure systems are urgently needed, at community and regional scales. This article develops a practical approach for analysts to characterize a community's infrastructure vulnerability and resilience in disasters. It addresses key challenges of incomplete incentives, partial information, and few opportunities for learning. The approach is demonstrated for Metro Vancouver, Canada, in the context of earthquake and flood risk. The methodological approach is practical and focuses on potential disruptions to infrastructure services. In spirit, it resembles probability elicitation with multiple experts; however, it elicits disruption and recovery over time, rather than uncertainties regarding system function at a given point in time. It develops information on regional infrastructure risk and engages infrastructure organizations in the process. Information sharing, iteration, and learning among the participants provide the basis for more informed estimates of infrastructure system robustness and recovery that incorporate the potential for interdependent failures after an extreme event. Results demonstrate the vital importance of cross‐sectoral communication to develop shared understanding of regional infrastructure disruption in disasters. For Vancouver, specific results indicate that in a hypothetical M7.3 earthquake, virtually all infrastructures would suffer severe disruption of service in the immediate aftermath, with many experiencing moderate disruption two weeks afterward. Electric power, land transportation, and telecommunications are identified as core infrastructure sectors.     

Disgusted subjects: the making of middle-class identities

Although the classed dimensions of ‘taste’ have, following Bourdieu, been widely discussed, expressions of disgust at perceived violations of taste have been less frequently considered in relation to class. This paper considers various expressions of disgust at white working‐class existence and explores what they might tell us about middle‐class identities and identifications. I argue that the narratives of decline and of lack present in such representations can be seen in terms of a long‐standing middle‐class project of distinguishing itself. Drawing on Bourdieu's critique of Kantian aesthetics, I argue that the ownership of ‘taste’ is understood as reflecting true humanity, and as conferring uniqueness. Ironically, however, this uniqueness is only achieved through an incorporation of collective, classed understandings. The paper calls for a problematization of a normative and normalized middle‐class location that is, I argue, given added legitimacy by a perceived decline in the significance of class itself. [A]n account of class, rank or social hierarchy must be thin indeed unless accompanied by an account of the passions and sentiments that sustain it (William Miller, The Anatomy of Disgust, p. 245). Social identity lies in difference, and difference is asserted against what is closest, which represents the greatest threat (Pierre Bourdieu, Distinction, p. 479). What we read as objective class divisions are produced and maintained by the middle class in the minutiae of everyday practice, as judgements of culture are put into effect (Beverley Skeggs, Class, Self, Culture, p. 118).