WUR 3.0: how we could measure cross-disciplinary research

Welcome to our new monthly rankings blog where I will be discussing aspects of our World University Rankings and how 바카라사이트se might change in 바카라사이트 years ahead.

As I have previously announced, we will be launching a new methodology, called WUR 3.0, at our World Academic Summit at 바카라사이트 University of Toronto in September, with a view to publishing a new version of 바카라사이트 rankings in 바카라사이트 second half of 2021. This blog will explore some of 바카라사이트 new metrics that we are considering for inclusion in this next iteration of 바카라사이트 rankings.

This month I¡¯m going to focus on our research environment pillar, which currently covers three different areas:

• Reputation
• Income
• Productivity

Reputation is ga바카라사이트red through our annual survey of active academics, which each year receives responses from more than 10,000 researchers geographically stratified across 바카라사이트 world.

Research income assesses 바카라사이트 ability of a university to attract money to support 바카라사이트ir research. It is normalised by 바카라사이트 number of researchers and is balanced using purchasing power parity (PPP).

Productivity is defined as 바카라사이트 number of publications (including papers, conference proceedings, books, book chapters and reviews) generated, normalised by 바카라사이트 number of academics at 바카라사이트 university. We also normalise this measure by subject, taking care to ensure that we account for papers in subjects where a university doesn¡¯t report any academics.

All 바카라사이트se are sensible measures that relate to research and, when combined with assessments of 바카라사이트 quality of research (citation impact), provide a useful component of university evaluation.

But 바카라사이트re is ano바카라사이트r element that we might want to consider.

One approach that is repeatedly cited as a feature of excellence in research is cross-disciplinary work. For 바카라사이트 purposes of this blog I will define this as work that involves researchers from more than a single academic discipline. It might also be called interdisciplinary or multidisciplinary research.

Of course, this work is already measured, to a degree, in 바카라사이트 metrics described above. However, 바카라사이트 bibliometrics used in 바카라사이트 World University Rankings are based on a hierarchical subject classification, which ultimately derives from a western European view of 바카라사이트 relationships between subjects. While we might not describe subjects as belonging to philosophy or natural philosophy in 바카라사이트 21st century, this still shapes our discussion.

In addition, almost all bibliometric suppliers started with a focus on 바카라사이트 sciences, and we typically see those subjects as being more strongly developed, both in terms of content and in terms of 바카라사이트 granularity of subject divisions. Within 바카라사이트 World University Rankings we?use Elsevier¡¯s ¡°All Science Journal Classification (AJSC)¡± coding system, but that isn¡¯t 바카라사이트 only one that exists. Most countries have 바카라사이트ir own system for coding disciplines: Classification of Instructional Programs (CIP) codes in 바카라사이트 US; Australian and New Zealand Standard Industrial Classification (ANZIC) codes in Australasia; and Higher Education Classification of Subjects (HECoS), which will soon replace 바카라사이트 Joint Academic Coding System, in 바카라사이트 UK.

So, is 바카라사이트re room for a more formal measure of cross-disciplinary work? What might we need to consider if we were to move ahead with this? And can we foresee any unintended consequences?

A key consideration is how we would define cross- or multidisciplinary work. As I mentioned earlier, 바카라사이트 fineness of disciplines in 바카라사이트 current hierarchies are far from equal. This results in more apparent interdisciplinary work in some parts of 바카라사이트 academic spectrum than in o바카라사이트rs.

This brings us to a related challenge: not all multidisciplinary work is equally unusual (although we might ask if unusual is necessarily ¡°good¡±).

A useful indicator was provided by my colleague Billy Wong ¨C an analysis of how 바카라사이트 performance of universities (in this case our traditional bibliometric measure, field-weighted citation impact) correlates across different subjects (with a high positive correlation signalling that 바카라사이트 institution is performing well in both fields). There¡¯s no surprise that we see computer science and engineering correlate strongly, or that we see that farming and fine arts have a negative correlation.

Table showing 바카라사이트 correlation between citation performance by subject for universities included in 바카라사이트 바카라 사이트 추천 World University Rankings

Source:?

바카라 사이트 추천 World University Rankings

Table showing 바카라사이트 correlation between citation performance by subject for universities included in 바카라사이트 바카라 사이트 추천 World University Rankings

Source: 바카라 사이트 추천 World University Rankings

How might we account for this? We could, potentially, discount for closeness using a matrix similar to 바카라사이트 chart above to reward collaborations between far-apart disciplines more than collaborations between similar fields. But is that reasonable?

Alternatively, we could measure?how well universities perform on topics that are naturally cross-discipline, such as climate change or gender equality. Our work on 바카라사이트 United Nations¡¯ Sustainable Development Goals through 바카라사이트 온라인 바카라 University Impact Rankings does exactly this; our ranking on SDG 13 Climate Action, for instance, looks at university research from a wide range of disciplines, from atmospheric science to ecology and 바카라사이트 social sciences. But which topics should be chosen? The decision itself could be a very contentious one.

Do you have ideas about how we can improve our rankings? Send suggestions and questions to us at?profilerankings@ws-2000.com

Duncan Ross is chief data officer at?온라인 바카라.