KEYNOTE SPEAKERS

Keynote lecture 1 - Tuesday 3 September 2019

Quantification – Its Affordances and Limits

 

 

 

 

 

 

 

 

 

 

John Carson, University of Michigan (USA)

Abstract

We live in a world awash in numbers.  Tables, graphs, charts, Fitbit readouts, spreadsheets that overflow our screens no matter how large, economic forecasts, climate modeling, weather predictions, journal impact factors, H-indices, and the list could go on and on, still barely scratching the surface.  We are measured, surveyed, and subject to constant surveillance, largely through the quantification of a dizzying array of features of ourselves and the world around us.  In this talk I will draw on work I have done on the quantification and measurement of intelligence to discuss some of the insights that these processes of quantification can bring, but also some of the perils that inevitably accompany them.  The story of how intelligence became a measurable quality and other examples from the history of quantification suggest that quantification and measurement should be seen not just as technical pursuits, but also as normative ones.  Every act of seeing, whether through sight or numbers, is also an act of occlusion, of not-seeing.  And every move to make decisions more orderly and rational by translating a question into numerical comparisons is also a move to render irrelevant and often invisible the factors that were not included.  The reductions and simplifications quantifications rely on can without question bring great and important clarity, but always at a cost.  Among the moral questions for the practitioner, I will suggest, is not just whether that cost is justified, but, even more critically, who is being asked to pay it?  Whose sight is valued, and what picture of the world results from foregrounding those forms of quantification as opposed to some others, or perhaps none at all?

 

Biographical Sketch — John Carson

John Carson is Associate Professor of History at the University of Michigan, where he has been since 1998. He received his PhD in History (of Science) from Princeton University in 1994, and has held postdoctoral fellowships from the Wellcome Institute for the History of Medicine, Department of Science & Technology Studies at Cornell University, National Humanities Center, Wellesley College Newhouse Center for the Humanities, Max Planck Institute for the History of Science, and Wissenschaftskolleg, where he was part of a research group on the history of quantification. His current research project explores the development and deployment of the medico-legal category “unsoundness of mind” (non compos mentis) in the eighteenth and nineteenth centuries in England and America. More broadly he is interested in the history of the human sciences, quantification, and the production of norms. His publications include The Measure of Merit: Talents, Intelligence, and Inequality in the French and American Republics, 1750-1940 (2007); “Mental Testing in the Early Twentieth Century: Internationalizing the Mental Testing Story,” History of Psychology 17 (2014); and “Every Expression Is Watched: Mind, Medical Expertise and Display in the Nineteenth-Century English Courtroom,” Social Studies of Science 48 (2018).

Keynote lecture 2 - Wednesday 4 September 2019

 

New developments in scientometric and informetric research

 

 

 

 

 

 

 

Mike Thelwall, University of Wolverhampton (UK)

Abstract

Abstract

This talk will discuss three recent developments that are changing scientometric practice: altmetrics, full text mining, and the impact agenda. After decades of research into altmetrics and webometrics, alternative indicators have emerged as a standard part of scholarly communication infrastructure. This can be seen in the availability of Altmetric.com scores in many publisher websites and the informal use of altmetrics supporting research evaluation narratives. Altmetrics are well enough understood that we can now recommend appropriate uses, and are ready to fully exploit them. Full text mining is a second development that is taking advantage of the increasing availability of collections of open access documents, such as the PubMed Central Open Access Subset, to get fine-grained information about citation contexts. This approach has the potential to identify important types of citation to get more precise evidence of the type of impact reflected by citation counts. The impact agenda in the UK Research Excellence Framework (REF) is the requirement for researchers to produce evidence-based narratives describing how their research has non-academic societal benefits. This has led to changes within UK universities to promote societal impact, such as through the appointment of impact officers. Altmetric and Webometric indicators are used as part of the evidence base of some of these narratives, which provide a tough challenge for scientometricians. The talk will finish with a few words about the importance of using research indicators responsibly. Practitioners should always be aware of potential biasing and systemic effects that can lead to unintended consequences.

 

Biographical Sketch — Mike Thelwall

Mike Thelwall, Professor of Data Science at the University of Wolverhampton in the UK, is the author of the cheap but excellent book Web Indicators for Research Evaluation: A Practical Guide. This book describes how to analyse altmetric and webometric data for research evaluation purposes, including appropriate methods for field normalising it and reporting it for use in evaluations. It is designed for scientometric researchers, practitioners and Master’s level students. Mike is also the programmer of the free but excellent scientometric software Webometric Analyst http://lexiurl.wlv.ac.uk, which includes hundreds of functions to gather and process scientometric, altmetric and webometric data. For example, if you already have a set of bibliometric records to evaluate, Webometric Analyst can add scores from Altmetric.com, reader counts from Mendeley, citation counts from Google Books, or syllabus citations from the web. With Webometric Analyst you can then summarise this data in various ways, including with tables of field normalised indicators and confidence intervals. Webometric Analyst is a bit confusing to use at first because of its range of capabilities but people that both study the book and use the program can expect long, productive and fulfilling scientometric careers.