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Chapter for Sarjit Kaur, Morshidi Sirat and William G. Tierney (eds.), Addressing Critical Issues on Quality Assurance and University Rankings in the Asia-Pacific
The global knowledge economy and the culture of comparison in higher education Simon Marginson Abstract. The global knowledge economy is associated with rapidly growing knowledge flows via the Internet. How is knowledge translated from the open source setting into formal processes and institutions so these secure coherence and a controlling role within the global knowledge-economy? If the k-economy consisted solely of commercial markets in knowledge then market values expressed in prices would suffice. But most knowledge has a public good character. Other mechanisms for valuation are needed. The chapter argues that knowledge flows are coming to be regulated by a system of status production that assigns unequal values to parcels of knowledge and arranges them in ordered patterns. The means of doing this are league tables and other institutional and research rankings; publication and citation metrics; and journal hierarchies. These processes together sustain the new standard of value. They have colonized the policy and public mainstream in just five years, securing massive momentum. The downsides are the normalizing character of these instruments in relation to mission diversity among higher education institution; and the subordination of all institutions in non English-speaking nations, and all those from developing nations. Implications for the research university in general, and for higher education in the Asia-Pacific, are explored. (Professor and Dr.) Simon Marginson Professor of Higher Education Centre for the Study of Higher Education The University of Melbourne phone: + 613 (03) 83448060 work phone: + 613 (03) 93170303 home phone: 0411541705 mobile fax: + 613 (03) 83447576 e-mail:
[email protected] CV and publications: http://www.cshe.unimelb.edu.au/people/staff_pages/Marginson/Marginson.html Centre for the Study of Higher Education 715 Swanston Street The University of Melbourne Victoria 3010, AUSTRALIA www.cshe.unimelb.edu.au/ 9702 words including abstract. Excludes above details on p.1, notes, tables and references.
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Introduction The last decade has seen an extraordinary expansion and intensification of Internet use. Between end 2000 and end 2008 worldwide Internet users increased from 361 to 1581 million. One quarter of the world’s people (23.4 per cent) are in the global network, including 17.2 per cent in Asia (internetworldstats 2009). In some countries over 70 per cent of households have personal computers. Broadband access was 25 per cent in OECD countries in 2006. Blogs are mushrooming exponentially (OECD 2008d: 55-62). Communicated information and knowledge is growing with unprecedented speed and magnitude, ushering in the global knowledge economy. World scientific publication in recognized journals is growing much more slowly, just 25.7 per cent between 1995 and 2005 (NSB 2009). There is a lag between new knowledge and its publication. Immediate publishing of research findings on the Internet is increasing rapidly. Actual academic knowledge grows faster than academic knowledge in the leading journals; and the larger field of communicated knowledge and information, embracing both academic and non-academic creations, is growing even faster again. The growth of knowledge has continued into the global recession. Unlike the financial economy and the industrial economy, the global knowledge economy is not exhaustively controlled by the boom/bust cycle of capitalist production. If ‘market’ means economic market it is a post-market phenomenon (though as will be discussed it is not a post-competition phenomenon). Of course knowledge production, particularly high science, is affected by material investments in research and communications infrastructure. While in all nations such investments are largely driven by public financing and sometimes by philanthropy more than by market forces, in some nations public investment has slowed during the recession because of reduced governmental capacity to pay. But most knowledge production is unaffected by fluctuations in the financial /industrial GDP economy. Still less is knowledge dissemination affected. Thus is sustained not by the profit motive but by the voluntary cultural activities of millions of interacting individuals and absorbs few economic resources. Once communications infrastructure is established it can carry a very considerable increase in traffic at low unit cost. One feature of the fast growing global knowledge economy is the rise of a global culture of comparison in higher education and research, the topic of the chapter and much of the book. The first annual rankings by the Shanghai Jiao Tong University Institute of Higher Education (SJTUIHE 2009) in 2003, followed by the Times Higher rankings which set out to put a
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British stamp on the emerging global order (Times Higher 2008), triggered a transformation of the higher education landscape. Comparative data vary in quality. Only some measures, all in the research publication and citation domain, can be classified as strong in social science terms. But in a short time global rankings and other comparisons have had a major impact on policies, strategies and behaviours in higher education around the world. Hazelkorn’s (2008) study for the OECD indicates that university leaders, governments, students and employers use them. Global referencing of universities is beginning to overshadow national referencing in many countries. The exception is the United States. US News and World Report rankings (USNWR 2008), focused on the national student market rather than standing in research or international attractiveness, still hold sway. While the US remains dominant in the global rankings it can afford to ignore them. Other nations are fixated on trying to catch up to the US. Global comparisons in higher education and research have two main functions. One is that they provide information. For example the more authoritative collections, such as the research performance rankings by Shanghai Jiao Tong, the Higher Education Evaluation and Accreditation Council of Taiwan (HEEACT 2008) and Leiden University (CWTS 2009), enable us to map the research performance of individual universities and national systems and this provides a useful proxy for research capacity and potential in the future, though data lags are a problem. Thus a pharmaceutical company looking for a research partner can narrow down the list of possible players on the world scale by using research output data. National governments see where their nation sits and which universities have a significant global role. The second function of the comparative data is more normative. They create global standards and encourage homogeneity on the basis of those standards, and penalize divergence and difference, while generating powerful desires for global recognition that together have accumulated as a rise in the importance of universities and research. Most league tables are limited to a top 200 or 500 institutions; though webometrics (2009) which emphasizes regional rankings, collects data for the world top 4000. The top 200 or 500 lists serve as a definition of ‘world class universities’,1 and of the rank order within the category of ‘world class’. Naturally all universities in the developed world want to maximize their rank within that category, and all emerging nations, and all leading research universities within those nations, want to be part of the category ‘world class’ and to rise as high as possible within it. But at any time there is room for only a fixed number in the top 200 or top 500; and if all universities around the world improve their performance by the same amount in proportional
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terms in order to lift their position in the rankings, then all ranks will remain the same. It is a status game and status games are always zero-sum. This makes it very difficult for new players to break into the top echelon unless they hyper-invest in higher education and research. Another problem is the lags between increased investment and improved ranking. The effect of global comparisons has been to generate a general trend to increased investment in R&D, even though such efforts are not always rewarded with early changes in rankings, coupled with intensive efforts in some nations to push up the rankings.2 Germany is investing in research concentrations in selected leading institutions. France has announced an ambitious merger program designed to improve its Jiao Tong performance. Other European countries are on the same path. So are Singapore and China through their government-driven investment programs, which pre-date the global rankings but are now informed by the ranking position. The expression of these trends in the Asia-Pacific region3 is highly uneven because of variations in the political economy of the region, and its cultural diversity. In both Internet publishing and formal codified science, universities in the United States are the dominant players, taking an incredible first 36 positions in the Leiden ‘Crown’ indicator which is the most authoritative measure of citation performance relative to institutional size4 (CWTS 2009); and the first 23 positions in the webometrics ranking which measures the volume of web-based publication (webometrics 2009). Nevertheless Asia-Pacific universities are increasingly important on the world scale. Shanghai Jiao Tong University has shaped the evolution of the knowledge economy itself. Japan has long been a major player in global research, with Tokyo University in most world top 20s; and China, Korea, Taiwan China and Singapore are on the up (see below). Australia has three universities in the second 50 of the Jiao Tong table. But while the ‘world class university’ movement beckons to all Asia-Pacific universities, few have the funding levels and personnel enabling them to compete effectively, and in an English language science system excludes swathes of non-English speaking Asia. Leading universities in their own national context such as Chulalongkorn in Thailand or Universitas Indonesia do not reach the world top 500 on research performance. From time to time Chula and some Malaysian institutions have figured in the Times Higher ranking due to good performances in the indicator for reputation. However, a ranking based on subjective reputation, without objective foundation, has limited credibility. Reputational data can change dramatically from year to year, depending on who is surveyed, political shifts, marketing and even gossip. A good position in the Times Higher ranking is a poisoned chalice when followed
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by a tumble out of the ranking the next year, and public disgrace, through no fault of the university (Marginson 2007). The status of ‘world class’ university needs a firmer foundation. But the point is that most global comparisons shut out the bulk of the Asia-Pacific. The chapter expands on these themes with some emphasis on the region. It aims to explain the potency of global rankings, which have gathered great momentum in a short time.
Globalization, the knowledge economy and higher education The global knowledge economy The global stock of knowledge is knowledge that enters common worldwide circuits (‘global knowledge flows’) and subject to monetary and non monetary exchange. It is a mix of (1) tradeable knowledge-intensive products, from intellectual property and commercial know-how to some industrial goods; and (2) free knowledge goods produced and exchanged on an open source basis. Commercial knowledge appears as a relatively small part of the whole (though the size of the whole eludes precise measurement). Together, the production, exchange and circulation of research, knowledge and information constitute the global knowledge economy or k-economy. The k-economy is distinct from the financial economy and industrial economy, and has its own laws of motion, while overlapping with the other economies at many points. Like all economy the global k-economy is a site of production. It is also social and cultural, a one-world community mediated by the Internet. K-economy activity is partly driven by commerce. Knowledge-inflected innovation has become central to industry and economic competitiveness. Basic research is an increasingly important element in policy discussions of industry innovation (e.g. OECD 2008c). But the global k-economy is not wholly contained by economic descriptors from the old industrial economy. The k-economy is partly shaped by status competition which has always been integral to research and research universities. And the k-economy is also about the semi-bounded system-driven anarchy of open source knowledge and cultural production, shading into social networking and the continuously forming global civil society. To understand not just the k-economy, but the times in which we live, it is essential to grasp the extraordinary dynamism of open source knowledge.
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In their form as ideas and know-how and works of art, i.e. as original goods; knowledge goods have little mass and require little industrial energy. They rest on human energy and time. Most such knowledge goods are digitally copied with minimal resources, energy and time. They also can be reproduced as mass commodities for sale, whereby they acquire prices and absorb more energy. The production of commercial digital goods is subject to scarcity. Freely created digital goods are not. There is no natural scarcity of knowledge goods. They multiply further in dissemination. The condition of freely produced and circulated knowledge goods is hyper-abundance not scarcity, very different to conventional industrial production. Thus the k-economy is powered by two heterogenous sources of growth. The first is economic commerce, which turns knowledge to its own purposes without exhausting the possibilities. The second is free cultural creation: decentralized, creative, chaotic and unpredictable freely circulating knowledge goods. Here the production and dissemination of knowledge goods converges with the extension of communications and expansion of economic markets. Manuel Castells (2000: 71) explains the economics of networks. The unit benefits of the network grow at an increasing rate because of an expanding number of connections. Meanwhile the cost of network expansion grows in linear terms. The cost of each addition to the network is constant. The benefit/cost ratio continually increases, so the rate of network expansion also increases over time until all potential nodes are included. Hence the extraordinary growth dynamism of open source ecology, which expands much faster than population or economic product; and its quasi-democratic tendency to universality. In turn the global roll-out of communications further stimulates commerce. The grid of the network metamorphises into a product market and a system of financial exchange. Meanwhile open systems posit more knowledge goods from beyond the trading economy. Some turn into commodities. Others posit further acts of creation, communicative knowledge catalyzing knowledge without mediation. The technological capacity to produce and exchange knowledge and cultural forms is possessed by growing numbers of school children throughout the world. It is much more widely distributed than the capacity to produce industrial goods. Interpretations of open source knowledge How might we understand open source knowledge? Paul Samuelson (1954) systematized the notion of ‘public goods’, non-rivalrous and non-excludable economic goods that are under-
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produced in commercial markets. Goods are non-rivalrous when they can be consumed by any number of people without being depleted, for example knowledge of a mathematical theorem. Goods are non-excludable when the benefits cannot be confined to individual buyers, such as law and order. Joseph Stiglitz (e.g. 1999) argued that knowledge is close to a pure public good. Except for commercial property such as copyrights and patents, the natural price of knowledge is zero. Stiglitz also noted that much of knowledge consists of global public goods. The mathematical theorem is useful all over the world. Its market price everywhere is zero. Faced with the Internet age, the first move of economists was to model the fast expanding stock of free knowledge goods simply as the source of commercial products. But most knowledge goods never become embodied in commodities. Even knowledge goods in their commercial form are a peculiar beast, being shaped by the logic of public goods. Knowledge goods are naturally excludable at only one moment, creation. The original producer holds first mover advantage. This provides the only solid basis for a commercial intellectual property regime. First mover advantage diminishes and disappears once commercial knowledge goods are placed in circulation and become non-excludable. Any attempt to hold down commodity forms at this point is artificial. Copyright is not just difficult to police, it is violated at every turn and impossible to enforce. In China the reward for academic publishing is not market royalties but enhanced status as a scholar. In India localized low cost copying, not commercial markets, leads the dissemination of digital goods. These approaches to knowledge goods, simultaneously pre-capitalist and post-capitalist, are more closely fitted to the character of knowledge and the open source ecology than is Western intellectual property law. Even so, though free knowledge goods are impossible as property in their own right, they have become increasingly crucial as the basis of innovations and profitable new products in all economic sectors. A university does not have to become a business in its own right, or sell the outcomes of its work in the form of commercial products, to be useful to private industry. The growing importance of open source knowledge has stimulated a change in policy thinking about university research. In Tertiary Education for the Knowledge Society (2008c: 102-103 & 120) the OECD shifted the primary focus of national innovation strategy in higher education from the creation of commercial intellectual property to creation and dissemination of breakthrough knowledge. Far more innovations derive from basic research, where curiosity driven researchers are free to follow their own pathways, than from all other forms of research combined. The important issue is to get that research into the knowledge systems as quickly as
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possible. When universities block the flow of knowledge through their own patenting arrangements they often retard dissemination. Universities should stick to what they and only they are best at ,which is curiosity-driven research, and the training of researchers for the whole k-economy. The main game in universities should be the production and dissemination of ‘open science’. This is a most important shift. It suggests the highpoint of the neo-liberal expectations about ‘academic capitalism’ (Slaughter & Rhoades 2004) has been passed and that national research systems will reduce the emphasis on revenue raising and business models of production and dissemination in research. Not that we are exactly on the brink of a new utopian era in higher education research in which external forces no longer rule the creative process. It seems that for every move to global openness there is an opposing move to secure closure. Global university rankings are one of the most powerful closures. Regulation of the value of open source knowledge Are all communications, cultural creations and public knowledge goods equivalent in value? Economics says yes. All have no price. But goods without market economic value may vary in other ways. Money is not the only medium in which the value of knowledge can be regulated. When knowledge passes through universities and publications systems it is structured so as to acquire new social meanings. Different ‘parcels’ of knowledge acquire unequal values. As every university president, rector or vice-chancellor knows well, the means of knowledge production are concentrated in particular universities, cities, national systems, languages, corporations and brands with a superior capacity in production or dissemination that pull the flows of knowledge in their favour. Knowledge is shaped and codified in research grant and patenting systems, research training; journals, books and websites; research centres and networks; professional organizations and academic awards. These processes are led from the principal centres of global knowledge power located mostly in the USA (Marginson 2008a). The institutional structures that regulate knowledge are visible but the key question is how they function in a coherent way on a worldwide basis. How do the chaotic open source flows of knowledge, with no evident tendency towards predictability let alone to equilibrium, become reconciled with national hierarchies, economic markets and institutions that routinely require stability and control in order to function? How is knowledge translated from the open source setting into formal processes and institutions so that these processes secure coherence
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and a controlling role within the global k-economy? If the k-economy consisted solely of commercial markets in knowledge goods there would be no need for any other system for translating knowledge into ordered values. Market values expressed in prices would serve the purpose. But most knowledge does not and cannot take the commercial form because of its public good character. Markets cannot do the job. Other mechanisms for valuation are needed. In the k-economy, knowledge flows are regulated by a system of status production that assigns unequal values to parcels of knowledge and arranges them in ordered patterns. The new means of assigning status value to parcels of knowledge are league tables and other institutional and research rankings; publication and citation metrics; and journal hierarchies. These processes together create and sustain the standard of value. This standard of value is a key mediating factor enabling the k-economy to interface with the financial and industrial economies, and with the systems for policy and regulation. It also enables the global keconomy to be mapped on a worldwide basis, identifying the concentrations of knowledge power, guiding investments in innovation by governments and business, and providing measures for the global k-economy comparisons that all nations seem impelled to make. This new global system for assigning standard value to knowledge has older roots. For a long time knowledge was structured in universities through semi-formal procedures and conventions. Institutional ranks and journal hierarchies operated by elite consensus and osmosis rather than transparent and universal metrics, and there were many different methods. It is only in the last half decade or so that modernized, systematic and accessible instruments have emerged to standardize the differing academic systems on a global basis. These instruments originated from the publishing industries, the Internet and in higher education itself, including research units specializing in the study of higher education and research outcomes, such as those at Shanghai Jiao Tong and Leiden Universities. In other words they began largely in globally focused civil society (Drache 2008). Governments are influenced by these instruments, and put them to their own uses, but for the most part did not invent them. Here again the global k-economy is the harbinger of a new epoch in human affairs, even while gaining part of its present impetus from the contest between nations as global competition states. Yet history is rarely linear. In moving beyond the market valuation of knowledge we have fallen back on traditional university status, led by venerable Harvards and Oxfords that pre-date the modern state. The k-economy is post capitalist but it is also pre capitalist.
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Status competition operates in a different manner to market competition. Status goods are goods of position in a finite hierarchy. There is an absolute limit to the number of status goods of high value (Hirsch 1976; Frank 1985; Marginson 2004). Only one university can be number one. Only 200 can comprise the top 200. Over time status competition becomes fiercer and those universities in strong starting positions, with grounded resources and reputations, tend to win. Hierarchy is both necessary to status competition and continually produced by it. Unlike the financial and industrial economies, in which the giants of yesterday such as Lehman’s or General Motors are the basket-cases of today, contestability in status markets is very limited. The same universities tend to maintain primacy for very long periods. In rankings and journal hierarchies existing institutional interests (and thus also Anglo-American national interests) are preserved. Status closure is more complete than market closure. It is its facility in the reproduction of hierarchy that fashions traditional university status as an instrument of closure strong enough to impose itself on the vast fecund diversity of global higher education. The research university in the global era The argument of this chapter suggests that in the k-economy research universities are subject to two systems for regulating value, that intersect only some of the time: the economic valuation of commercial knowledge as represented by intellectual property and knowledgeintensive products; and the status value of public good knowledge as determined by university rankings, and research and publication metrics. Universities have most of their eggs in the second basket. Only a small portion of knowledge generates surplus revenues. All knowledge can generate prestige that enhances the relative position of institutions within the k-economy. Nevertheless measures of the status of knowledge are applied to only those parts of knowledge codified in refereed papers, monographs and other formal mechanisms. Beyond published academic research and commercial research is a third category outside value regulation; that part of research, scholarship, ideas and other knowledge and information created in universities and elsewhere whose value remains uncodified, works part of the open source domain that are neither sold in a market nor counted and ranked for status. This knowledge has the potential to feed into the formal academic domain. Much of it never finds its way there. Some feeds straight into the commercial domain, in consulting and ‘quick and dirty’ research, without undergoing academic valuation. The research university is driven
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three ways: by the commercial imperative, by the formal system for assigning status values to knowledge which is partly under university control, and by the unpredictable swirlings of open source knowledge which no-one controls. The three heterogenous ‘systems’ intersect untidily and have differing implications for institutional forms and academic behaviours. These dynamics play out differently, depending on type of institution and on the capacity of the national higher education system to participate in the primary knowledge flows. Elite universities are sustained not by their function as accumulators of revenue, in the manner of a business, but by their function as accumulators and producers of status: their own selfreproducing status as institutions at the peak of their societies, and in the case of the Harvards and Oxfords the peak of the knowledge economy; the status of the knowledge they produce and codify; and the status they transfer to their students. Revenues are important but as a means to an end rather than the final bottom line. Status competition dominates at the peak of the global sector and in the large national systems. As we pass down the hierarchy university status becomes emptied out; the institutions play a diminishing role as producers of formally sanctioned research, though their personnel may contribute to open source knowledge; and the accumulation of revenues becomes more desperate and more determining of the mission. This recalls Pierre Bourdieu’s (1984; 1988; 1993) notion that the field of higher education is structured by a polar opposition between two types of institution with two different logics. At one end there is the sub-field of restricted elite production. At the other end is the sub-field of mass production tending to commercial production. Each sub-field has its own distinct principle of hierarchization. In the aristocratic elite universities, where the high value products are immersed in knowledge and power and shaped as tools of advantage, the principle of hierarchization is that of cultural status and is autonomous and specific to the field. In the mass institutions the hierarchy is shaped by economic capital and market demand, and the institutions are heteronymous.5 Between these two sub-fields lie a range of intermediate institutions combining the two opposing principles in varying degrees. Thus in global rankings systems the peak institution, the idealized model, is the elite Anglo-American research university. This kind of university provides the template for the Jiao Tong ranking. The other institutional type which exercizes some policy influence as a global model, though not in global rankings, is the mass for-profit vocational university of the Phoenix type. This is the opposite pole in Bourdieu’s imagination. Bourdieu provides a penetrating explanation of the dynamics of status in higher education. Arguably, however, his theorization does not capture
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the dynamics of open source knowledge, which partly cut across the status hierarchy. Further, commercial imperatives play a larger role in the elite universities than he suggests: for example, leading universities are more liable to create intellectual property in new science. How functional is the system of status allocation for commerce and industry? On one hand, some especially in the USA understand status competition in higher education simply as an economic market. It is true that global rankings extend comparison to all institutions in all countries. Those outside the rankings are also defined by them, being placed in a subordinate position. But they do not necessarily bring all into a common competition, let alone a single economic market. Global rankings unite disparate universities from Toronto to Amsterdam to Lima to Kabul to Hanoi. Yet most universities do not compete directly with more than a handful of others for students below doctoral level; many do not compete with each other in relation to commercial knowledge; and some do not compete in the global research circuits at all. What they share is the global knowledge economy that university and research rankings help to make coherent. In other words the communicative network extends much more broadly than does any specific economic competition. Within the communicative network status competition extends further than economic market competition. Rankings are more and less than a means of market formation. Rankings create and reproduce competitive behaviours. Rankings information feeds into the fee-based market in international education, a burgeoning $40 billion a year global industry. Status hierarchies structure economic competition. But they also block new and aspiring entrants; and rankings serve collaborative as well as competitive purposes, guiding universities in different countries in patterns of cross-border association. On the other hand much analysis of research in elite universities is focused on ongoing tensions between commerce and academic values (e.g. Bok 2003), implying that economic markets and knowledge status are constantly at loggerheads. Such tensions are obvious. Their significance is more debatable. The commercial portion of research is economically significant but constitutes a relatively small part of research revenues and time in higher education. Perhaps the more important tension is between open source knowledge production, and the status hierarchy in knowledge that is fostered by rankings and metrics. Status competition implies closure. It reproduces university hierarchies at both national and global levels. Open source ecology fosters openness, its borders are porous and flexible, it moves into new areas of activity in response to demand. In the open source domain language of use is an issue for non-English speaking countries; public knowledge goods are no less likely than private goods
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to reproduce global cultural hierarchy. Nevertheless the open source domain is open to innovations from anywhere. In the longer run this destabilizes the ranked hierarchy and creates space for new players. The global hierarchy is steep. But no closure is complete forever.
The mechanisms University rankings The first mechanism to secure a coherent global role was holistic university ranking. So far the Shanghai Jiao Tong University ranking is the one ranking which is both broadly used and credible as social science. It relies on existing data immune to university lobbying or national government influence. The methodological weakness of the SJTUIHE ranking is dependence on Nobel Prizes for 30 per cent of the index. The Prize is submission-based and partly reputation driven and lacks objectivity as a measure of stellar science. Further, the Nobel indicators reward the universities of training and current employment not the university where the discovery was made. The rest of the Jiao Tong index is defensible: the number of leading (‘HiCi’) researchers as measured in citation counts, articles in Science and Nature, publication in leading disciplinary journals; and these outputs on a per faculty basis. Jiao Tong ranks universities across all fields of research except the humanities and creative arts, in five broad disciplinary fields, and in sub-fields in the Nobel Prize disciplines. The Jiao Tong Institute’s ranking is a remarkable achievement in which an Asia-Pacific university has shaped the global higher education order and created benchmarks for global comparison: measurement of real outputs rather than reputation, and transparent and accurate data collection. It has hastened the evolution of the k-economy itself. The fit between performance, data and ranking position is strong enough for nations, universities and doctoral students to use the Jiao Tong position as a guide to planning and investment. But the measures are biased in favour of English language nations, big science and medical universities. Jiao Tong reproduces the existing hierarchy.6 With the exception of Japan and Australia which have mature research systems, AsiaPacific nations do not perform strongly in the Jiao Tong ranking. This may change. From 2004 to 2008 the number of Chinese universities in the Jiao Tong top 500 rose from 12 to 23.
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[Insert Table 1 about here] Asia-Pacific universities in the Jiao Tong top 200 are: in Japan Tokyo (19), Kyoto (23), Osaka (equal 68), Tohoku (79), Kyushu, Nagoya and Tokyo Institute of Technology (101-150 group), Hokkaido and Tsukuba (151-200 group): in Australia the Australian National University (59), Melbourne (73), Sydney (97), Queensland and Western Australia (101-150 group) and New South Wales (151-200 group); the National University of Singapore (101-150 group); Seoul National in Korea, and the National University of Taiwan (151-200 group). The Jiao Tong was followed by a ranking by the Higher Education Evaluation and Accreditation Council of Taiwan (HEEACT 2008). It provides a larger set of research indicators reconciled in a composite index and a single league table. The individual indicators are informative but the Taiwan exercise lacks the simplicity and first mover advantage of the Jiao Tong. The Times Higher ranking is widely known, and encompasses a broader set of indicators than just research (THES 2008). But it lacks credibility because of the poor response rate to its survey of university reputations, the fact that universities from the UK and former British Empire countries do exceptionally well in league table and many changes in data compilation that have contributed to extreme volatility.7 The suspicion is that Times Higher methodologies are adjusted to alter the position of particular universities. The Times often elevates leading national universities in individual countries above their level in other tables, augmenting its worldwide marketing. But a poor fit between changes in university performance and changes in Times ranking (Marginson 2007) undermines the utility of this ranking for the k-economy. The global ranking of the top 430 universities issued by a Russian group in March 2009, based on a large set of indicators, is unlikely to gain traction. Uniquely it places Moscow State University at number five in the world, one place above Harvard; and there are 69 Russian universities in the world top 430 (RatER 2009). All other global rankings based on research outcomes or composite indicators confirm a similar group of universities in leading positions. Webometrics ranks the communications power of universities in the k-economy. It records the number of webpages, external hits, ‘rich pages’ such as pdfs and word documents attached to websites, and publication and citation counts in Google Scholar. The last constitutes 50 per cent of the index. Thus there is a strong element within the ranking derived from the formal publication world but it also picks up elements in the open source domain, thereby partly undercutting the orthodox allocation of academic status.
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The Web covers not only formal (e-journals, repositories) but also informal scholarly communication. Web publication is cheaper... It could also reach much larger potential audiences, offering access to scientific knowledge to researchers and institutions located in developing countries and also to third parties (economic, industrial, political or cultural stakeholders) in their own community (webometrics 2009) Webometrics was developed primarily to encourage web publication of academic data as the most direct and accessible form of dissemination. Presented as a ranking system, it flies the flag for open source knowledge.8 Nevertheless, the same institutions that dominate formal science also lead informal academic publication, communicative capacity is even more concentrated than research capacity, and being an English-speaking country appears more of an advantage in webometrics than the Shanghai Jiao Tong. The US universities in the first 23 places are led by MIT, Stanford and Harvard. In the Asia-Pacific Australia has 13 of the webometrics top 500, Japan 10, China including Hong Kong 10, Taiwan China 10, Korea 4, Thailand 3, Singapore 2, New Zealand 2 and India 1. Asia-Pacific universities in the top 200 are listed in Table 2. Universities from Taiwan China perform exceptionally strongly in the webometrics ranking, with nine of the first 400 places, led by National Taiwan University at 55 in the world. Japan and China are weaker in webometrics than research rankings, though Peking University is an exception. Indian institutions are weak in the webometrics first 500 despite the Indian IT industry and widespread English usage as a second language. If the capacity of universities in the global knowledge economy is a combination of communications power and research power, Table 2 is a useful compilation of the global knowledge power of the Asia-Pacific universities. It is a raw volume measure with no control for institutional size. [Insert Table 2 about here] Publication and citation metrics The Jiao Tong ranking helped to bring bibliometric data on research and citations, including impact measures and judgements about the centrality and quality of field-specific journals, into the policy mainstream. The field of data compilation involves two major publishing
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houses and researchers in many nations specializing in science indicators. In 2007 Leiden University in the Netherlands announced a new ranking system based on its own bibliometric indicators, using four rankings of institutions: total numbers of scientific publications; average academic impact measured by citations per publication; average impact measured by citations per publication modified by normalization for academic field, i.e. controlled for different rates of citation in disciplines, called the ‘brute force’ indicator because it rewards large institutions for size; and the last measure modified to incorporate normalization for size, which the Leiden group calls its ‘crown’ indicator (CWTS 2009).9 The Leiden group published its first global ranking in 2008, incorporating publication and citation data for 2003-2007. Arguably the Leiden indicators are the best comparative data on formal research performance so far, though like all such metrics they block recognition of innovations in field definition and new journals. The ‘brute force’ indicator measures quantity research power in global science. The ‘crown’ indicator incorporates an element of quality, enabling boutique universities to be identified. In the table for the ‘brute force’ indicator Harvard more than doubles the citation volume of the next university, the University of California at Los Angeles. US universities constitute 28 of the first 40. The UK, Canada and Switzerland perform well. In the Asia-Pacific Japan has 8 of the top 200 universities including 4 of the first 50. Australia has 7, China including Hong Kong 5, Korea 3, Singapore 2 and China Taiwan 1. Table 3 lists the universities. This is an excellent indicator of institutional weight in the formal academic sector of the k-economy. [Insert Table 3 about here] In relation to the Leiden ‘crown’ indicator, as noted US universities hold the world’s first 36 places. MIT, Princeton, University of California Berkeley and Stanford rank ahead of Harvard. Universities from Switzerland and the Netherlands emerge strongly, the latter doing better in this measure than others. Of the Asia-Pacific Universities first place goes to the University of Hong Kong at 117 followed by the Australian National University at 120, Melbourne at 154, Queensland at 159, Tokyo down at 160, New South Wales at 163, National University of Singapore at 164, Osaka at 171, Sydney 175, Kyoto at 180, Auckland at 185, Western Australia at 187, the Korean Advanced Institute of Science and Technology at 190, Monash at 192 and Tokyo Institute of Science and Technology at 200. Australia has 7 universities in the top 200 and is stronger than Japan with 4, followed by China Hong Kong,
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Singapore, New Zealand and Korea which each have 1. Seoul National is outside the top 200 at 203. Highest placed university on China’s mainland is Peking at 228 but there are seven more institutions from China in places 234-249, and nine from Japan in places 202-238.
Comparison, diversity and inequality Comparison and diversity There is no one single ‘Idea of a University’ (Newman 1899/1996). There are many different missions, structures and organizational cultures, associated with distinctive traditions and models of higher education. All of these multiple ‘Ideas’ are nested in historical and national contexts, and have specific conditions of possibility. In the Westminster countries (UK, Australia, New Zealand) national systems combine university autonomy with explicit central steering. American private universities are self-steering with an enterprising presidency and strong faculty traditions; public universities have parallel academic cultures but the state legislature is an additional point of accountability, of varying importance; and both public and private universities have been shaped by federal research funding and by the market in students underpinned by the federal loans scheme. Below the research universities there is a long list of institutions with more localized missions; and a for-profit sector where university autonomy and academic freedom are largely absent. The Nordic/ Scandinavian university combines emphases on high participation social equity, research culture and university autonomy with strong state investment (Valimaa 2004; 2005). The German-style university opts for elite participation, research culture and state administration. The Latin American public university has high participation, scholarly culture and a central social and political role in the building of the nation-state. The emerging science universities of East and Southeast Asia, including China, Taiwan China, Korea and Singapore are fostered by state investment. In Singapore the mission of the two leading research universities is grounded in an explicitly global strategy. India, which combines a multiplicity of regional traditions as complex as Europe, provides both orthodox scholarly universities and business-focused institutions that at the best combine high quality with commercialism. Beyond the research university are strong vocational sectors in Finland, Germany (the Fachhochschulen), France, and other vocational
18
and community-based programs. There us a growing number of online institutions. There are also many specialized institutions in one or another field of teaching and research. However, most ranking systems rest on a dominant ‘Idea of a University’ grounded in the comprehensive English speaking Anglo-American science-intensive institutions. This has become the model for the ‘World Class University’ (SJTUIHE 2009) or ‘Global Research University’ (Marginson 2008b) in this era. A principal concern about league-table rankings is that they are biased against institutions and national systems that do not fit the model, while over time driving all institutions towards comformity with the criteria that govern ranking performance. Like all comparisons, rankings have standardizing, normalizing effects. In other words, rankings confront the diversity of global higher education and begin to reduce it, while at the same time suborning non-English speaking institutions, institutions without big budget science, predominantly teaching or access focused institutions; vocational institutions and specialists. In a single league table led by Harvards and Oxfords these effects are pronounced. On the question of language bias Altbach remarks that: ‘The fact is that essentially all of the measures used to assess quality and construct rankings enhance the stature of the large universities in the major English-speaking centres of science and scholarship and especially the United States and the United Kingdom’ (Altbach 2006: 3). Front rank scientific publication is almost exclusively in English and the formal systems for applying status to knowledge are English language systems. On the other hand open source knowledge permits and produces greater plurality. English is no longer the majority language of the Internet. Institutional classifications If institutions are separated into different classifications on the basis of mission they can be compared with their fellows. This in turn enables a more accurate identification of value and of the worldwide distribution of capacity in the k-economy. Classification creates allows the expression of several different hierachies rather than one universal hierarchy of institutions; though one hierarchy of value, that of research intensive universities, tends to be dominant. Classifications of institutions are used in the United States (the Carnegie classification) and China and one is being developed for the 3300 higher education institutions in the European Union and 4000 in Europe as a whole (Bartelse & van Vught 2007: 9; van der Wende 2008). Discussions have begun on the possibility of developing a global classification
19
of higher education institutions, which could could address the problem of diversity of mission. A single global classification system would not address the problem of cultural bias. This can be tackled thorough creation of more specific regional or language sets for rankings purposes; for example all Spanish-language instituions, all Southeast Asian institutions. Comparison and inequality The problem is not simply one of cultural bias. There is also the gulf in material terms between universities in the Anglo-American region and those in much of the Asia-Pacific. Essentially university and research rankings provide a means of assigning primacy, and identifying strength within the world, of the high cost science university in Anglo-America, Western Europe and parts of Asia, plus a small number of standout institutions (most of them designated national research universities) in Russia, Mexico, Brazil and Argentina. But how useful is it to apply the same criteria and measures to research universities in nations with a GDP upwards of $30,000 USD per head, and nations with a GDP per head of less than $10,000 per year, or less than $5000 per year? Of the top 500 universities in the Shanghai Jiao Tong ranking in 2006, just 21 (4.2 per cent) were located in nations where per capita GDP was below the 2005 global average of $9420 (World Bank 2009): 14 in China excluding Hong Kong and Taiwan, 4 in Brazil, India 2 and Egypt 1. At the top of the hierarchy the link between research capacity and economic strength was even more apparent. All but one of the top 100 research universities were in nations with per capita incomes of over $19,500 in 2005.10 This excludes all of the Asia-Pacific except Japan, Australia, New Zealand and Korea.11 An example: The case of Vietnam Take the case of Vietnam. In 2007 its per capital Gross National Income was $2550 compared to the world average of $9852 and the well over $40,000 in the USA (World Bank 2009).12 Vietnam is still recovering from is called there the ‘American war’ that was won in 1975. Even in terms of a low national income base Vietnam under-funds tertiary education. Nevertheless, global university rankings have energized policy makers in Vietnam as elsewhere. On 27 July 2008 the Prime Minister signed a government decision on the Vietnam
20
Higher Education System Planning Period for 2006-2020, which included the projection that by 2020, at least one university from Vietnam would be listed in the world’s top 200 universities. (It was not specified which top 200 listing would be used as the template). In abstract the policy goal might seem appropriate. High capacity research universities are essential points of connectivity in the global k-economy, underpinning the global effectiveness of the nation in terms of government, economy and cultural projection and reach. However, given the state of higher education and the level of national wealth in Vietnam, if the goal is defined in terms of a reputable top 200 list such as that of Shanghai Jiao Tong then it is so far from realization that it is inconceivable it could be achieved in the time frame proposed. In total 30 per cent of the Jiao Tong index is determined by the number of Nobel Prize winners on staff, or educated by the University (SJTUIHE 2009). The great majority of the top 100 universities and many listed at 101 to 200 are associated with at least one Prize winner. There have been practically no winners of the science and economic prizes at universities in the developing world.13 Another 20 per cent is determined by the presence of HiCi researchers, researchers on the staff of the institution who are listed in the top 250-300 in their field of study on the basis of citations in leading English language research journals. With the exception of Moscow State University, very strong in Nobel Prize winners, and the University of Buenos Aires in Argentina, all top 200 Jiao Tong research universities have HiCi researchers. Most have several. Harvard has more than 300 such researchers. There are nearly 4000 in all American universities. In Asia-Pacific only Japan and Australia have more than 100 HiCi researchers. Korea, Singapore and China will have more in future years. To attract and/or hold a critical mass of HiCi researchers universities in Vietnam, the country would need to offer close to global salary rates, and also infrastructure support, including personnel and equipment, that was competitive in world terms. This would require a large scale, concerted and sustained investment in universities designated for such development. Further Jiao Tong criteria relate to the publication of scientific papers in the leading journals Nature and Science (20 per cent) and overall citation performance (20 per cent). Here HiCi researchers sustain a strong performance. Vietnam has had at least one article in Nature, but with just over 200 scientific papers per year its universities are not in a position to compete for the Jiao Tong top 500 on the basis of publication and citation volumes. If a China-style accelerated investment in R&D was implemented in Vietnam – unlikely given that Vietnam’s per capita income is less than half that of China’s and the growth rate is slower - it would take
21
5-10 years before rates of publication took off and another decade before this fully showed in citation counts. The experience of China and Korea indicates that the achievement of a critical mass of HiCi researchers, including the return of many Vietnamese scholars working abroad and a partial reversal of the ongoing pattern of ‘brain drain’, would take 15-20 years. For any university in Vietnam the pathway to a top 200 Jiao Tong ranking would be a long slow one. Such an achievement would require a permanent shift to European levels of funding and academic salaries, which simply is not on the national policy radar at this stage; and even after two decades Vietnam would be approaching the Jiao Tong top 500 not the 200. A more realistic but still very difficult goal would be achievement of a top 500 Jiao Tong university by 2030. China has yet to reach the Jiao Tong top 200 though it has 18 universities in the top 500. Vietnam might have defeated the US in war and gained independence, but the rubric of the global k-economy is not national defence. It is capacity plus connectivity. Here US higher education retains a decisive advantage for a long time to come. It is a dilemma for developing countries. All nations must avoid knowledge dependency if they can. Increasingly, the expression of self-determining national identity will require the nation to have an advanced capacity in higher education and research. Yet it is hard to justify the levels of investment required, investment with few direct beneficiaries, against priorities such as basic health, basic education, urban infrastructure, communications and transport. At a higher level of material development, ‘world class’ k-economy investments become feasible, as Korea’s trajectory shows. Until that stage is reached, global university and research rankings are meaningless for the government and for the institutions of the nation concerned. Such comparisons have little function except to inflate policy goals to unrealistic levels or to inculcate pessimism. How the Asia-Pacific nations are positioned Where does all this leave the Asia-Pacific? In the process of comparison and valuation institutions in Australia and New Zealand have an advantage. Singapore and Hong Kong also benefit from facility in English, plus strong state investment. No other nation in the region competes on equal terms with the English speaking countries. However the leading research universities of Japan, Korea, PRC China and Taiwan China have been organized so as to largely fit the global model and all four systems are now significant players in published research. In Japan national spending on higher education is the third highest in the world and
22
the nation is a research powerhouse. though its universities under-perform relative to resources when compared to English language and European universities. China, Taiwan China and Korea, have made remarkable gains, as has Singapore. These four are the new ‘innovation tigers’ and they are moving up both university rankings and publication/citation comparisons. Table 4 sets out the rate of growth of scientific publications in the Asia-Pacific in 1995-2005. [Insert Table 4 about here] In universities in all nations outside the tiger group; and to a degree in China, Taiwan, Korea and Japan; the modest distribution of highly developed English language skills reduces the capacity to interact, to disseminate and especially to produce works of highest acuity and authority for global journals. As more personnel in these universities acquire advanced bilingual skills capacity will improve. Emerging scholars possess such skills more often than their elders. But for the foreseeable future all non-English speaking nations are handicapped in rankings of the present type. At the same time work produced in national languages, which are central in the humanities and some social sciences, will become increasingly undervalued at home while ignored by the global k-economy. Relatively little work even in major European languages other than English is translated into English and made universally available (Held et al. 1999: 346). Work in Bangla, Bahasa, Tagalog, Thai, Viet, etc. is rarely so translated. Notwithstanding the language factor Thailand might eventually enter the tiger group. Though state policy is not as focused, published science is growing rapidly. The increase in science papers in India has been modest, more so given that skills in English are widespread in South Asia, though output quickened in 2000-2005. The Malaysian government talks up R&D and its higher education spending as a proportion of GDP is relatively high but its university research performance is disappointing, perhaps because a high proportion of public funding is absorbed by student support, and policy is overly focused on commercial applications of research at the expense of basic research capacity. The other countries are more marginal to the world science system. Vietnam shows the best rate of improvement since 1995. In Indonesia, the Philippines and Bangladesh, countries with nearly half a billion people between them, there has been little increase in participation in the global flows of research knowledge.
23
Concluding remarks The systems for measuring and valuing knowledge mostly do not involve prices. Academic capitalism is not the principal driver of global comparison. However, university rankings and research metrics are functional for commercial interests in their efforts to draw financial value from knowledge, and sharpen competition between institutions: in an era in which the idea of capitalist markets is central to the common global culture, university rankings thereby feed into imaginings of higher education as a global economic market. This idea takes tangible form only in competition for full fee paying international students, in which producers aim to maximize unit revenues, profitability and market share and expand so as to meet demand. Competition in research does not function like this. For the most part worldwide higher education is a competition for prestige and global influence rather than a competition for revenues. Rankings and research metrics vector that competition, creating a hierarchy that is functional not only for business and industry but for governments and civil society, including students and families. The system of valuation guides navigation of the k-economy. It also subordinates most institutions, and all developing nations, within it. One dilemma facing all nations is how to situate the contribution of non research-intensive higher education institutions, simultaneously elevated by the extension of learning and credentialing functions across societies, and weakened by the lack of research status. And in the Asia-Pacific the valuation of knowledge and knowledge producers informs the innovation tigers of progress in their upward trajectory within the world but it holds other institutions and countries down. The issue for theorization and empirical investigation is that of the emerging relations between three overlapping domains of practice: that of open source free knowledge flows, potentially non-hierarchical though language of use is power-forming; that of status goods where older university and national/imperial hierarchies become determining; and that of knowledge and higher education absorbed into the money economy, academic capitalism. The last is secondary but never out of the picture and helps tether universities to other centres of power. These three domains are in unstable symbiosis. Further rapid and unpredictable changes can be expected, akin to the fecund evolution of global rankings since 2003. Research capacity and performance, which largely means work in the natural sciencebased disciplines, always central to understandings of university status and productivity, are more so now. For emerging and developing nations it seems increasingly urgent to build
24
‘world class’ research universities. At the same time the manner in which global rankings are configured is a hot topic. Rankings and the associated processes have created a new policy space for global discussion in which civil organizations like the North American Education Policy Institute mix with social scientists of ranking and state and semi-autonomous agencies, especially in Europe and East Asia. Both OECD and UNESCO have been active in the international conferences on ranking. So far these discussions have yet to devise a multilateral solution to the unilateral global effects of rankings, that elevate US and to a lesser extent UK higher education above the rest in a manner that near-universalizes university failure and negates the democratizing potentials of a world in touch with all of itself for the first time. Though rankings will always elevate and reproduce the power of the already strong, the comparisons could be reworked to incorporate greater plurality of language, institutional type and mission. A lesser use of composite indicators and league tables would be another step forward. The more space for heterogeneity of valuation, the better. The way out from under the savage hierarchical effects is to break down the single worldwide table of universities with specialist and pluralized comparisons, with rankings by institutional mission, by discipline, by culture and language and geographical region, and by intra-universal mission; and with rankings not only on research output but on research application and impact, teaching quality, learning outcomes, and local and global institutional engagement. This would enable a more complex but also a more transparent and informative mapping of the k-economy, in which purposive decisions could be more precisely targeted. In the Asia-Pacific regional and subregional (e.g. ASEAN group, East Asian) rankings would be less pejorative than global rankings and enable more meaningful policy targets. Regional rankings would also be a useful aid to industry and students especially if based on a regional classification of institutions. Perhaps the ultimate answers lie in the domain of open source knowledge beyond standard rankings and metrics. The more creativity is sustained and communicated outside orthodox academic research and publishing, the greater the potential for ‘flat’ and plural relations and the more the knowledge economy starts to morph into its potential successors, which are the creative economy and the society of ideas and design (Peters et al. 2009); and more that the non traditional producers of global knowledge can enter the conversation.
25
Notes
1
To use the terminology deployed by Nian C. Liu at Shanghai Jiao Tong University (SJTUIHE 2009).
2
Naturally institutions shape and present themselves so as to maximize their position in the comparative
indicators, though once data are standardized in a rankings friendly manner, such efforts have diminishing returns. 3
The Asia-Pacific region is understood here as the long arc of countries from Pakistan to Japan, including the
small Western Pacific nations but excluding central Asia and the Middle East. 4
The University of Cambridge in the UK is first in the rest of the world at 37 (CWTS 2009).
5
Though from time to time mass institutions renew themselves using ideas drawn from the elite sector.
6
Another problem is that the Jiao Tong league table is often read as a world’s best university list, not a research
list. This is unfortunate but hard to stop, especially in the absence of a credible all-round measure of performance that includes teaching and/or student learning (Dill & Soo, 2005). Following the policy impact of the its PISA comparisons of school achievement, the OECD is running an Assessment of Higher Education Learning Outcomes (AHELO) project designed to establish comparative measures of learning outcomes from higher education (OECD 2008a; 2008b). Such comparisons could have profound impact. The principal measures of comparative learning outcomes have been surveys of students or graduates. These are likely to develop further (CHE 2008; Usher 2008) but are limited by their subjective character. The AHELO project is piloting measures of the generic skills of graduates, of graduate competence in two disciplines (engineering and economics), of graduate employment outcomes. It also collects contextual data to assist in interpretation. It is envisioned the units of comparison will be individual institutions rather than national systems. The exercise does not cover all outcomes of teaching and learning. Formidable technical and policy obstacles remain. But there is much policy momentum in favour of solid comparisons of the outcomes of teaching and learning. If joined to research rankings, they could be used to develop a combined ranking of teaching and research performance. 7
Other problems with the Times Higher ranking are the use of a quantity indicator (student-staff ratios) as proxy
for teaching quality, and the student internationalisation indicator which rewards student quantity not quality. 8
‘We intend to motivate both institutions and scholars to have a web presence that reflect accurately their
activities. If the web performance of an institution is below the expected position according to their academic excellence, university authorities should reconsider their web policy, promoting substantial increases of the volume and quality of their electronic publications’ (webometrics 2009) [original emphasis]. 9
Compared with the Jiao Tong ranking the Leiden CWTS has dispensed with Nobel indicators, counts of leading
researchers and a composite indicator based on arbitrary weightings. 10
The exception was Moscow State University.
11
Per capita income data for Taiwan are not available.
12
Data expressed in Purchasing Power Parity terms, i.e. adjusted for the buying power of the local currency.
13
Winners of the Nobel literature and peace prizes are not included in the SJTUIHE count.
26
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31 Table 1. Asia-Pacific universities in the Shanghai Jiao Tong University top 500, 2008 Number of universities in the Shanghai Jiao Tong top: 100
200
300
400
500
Japan
4
9
12
18
31
Australia
3
6
9
14
15
Taiwan China
0
1
1
4
7
Korea
0
1
3
7
8
Singapore
0
1
1
2
2
China including Hong Kong
0
0
10
12
23
New Zealand
0
0
2
3
5
India
0
0
0
2
2
total
7
18
38
62
93
Source: SJTUIHE 2009
32 Table 2. Asia-Pacific universities in webometrics top 500 University
Nation
Position
Australian National U
Australia
48
U Tokyo
Japan
52
National Taiwan U
Taiwan China
55
Kyoto U
Japan
78
Monash U
Australia
111
Peking U
China
117
U New South Wales
Australia
120
U Hong Kong
Hong Kong China
121
U Queensland
Australia
127
U Melbourne
Australia
130
National U Singapore
Singapore
135
Keio U
Japan
152
Chinese U Hong Kong
Hong Kong China
156
National Chiao Tung U
Taiwan China
179
Seoul National U
Korea
182
Korea Advanced Institute of S&T
Korea
204
Nagoya U
Japan
216
U Auckland
New Zealand
239
Osaka U
Japan
240
Tsinghua U
China
241
U Adelaide
Australia
248
Tsukuba U
Japan
260
National Taiwan Normal U
Taiwan China
273
National Cheng Kung U
Taiwan China
274
National Sun Yat-Sen U
Taiwan China
282
Tohoku U
Japan
289
Prince of Songkla U
Thailand
295
National Tsing Hua U Taiwan
Taiwan China
308
U Western Australia
Australia
318
Tokyo Institute of Technology
Japan
343
Kyushu U
Japan
348
Queensland U of Technology
Australia
353
Shanghai Jiao Tong U
China
355
Chulalongkorn U
Thailand
369
33 National Central U
Taiwan China
370
Royal Melbourne Institute of T U
Australia
371
Pohang U of S&T
Korea
372
Macquarie U
Australia
376
Kobe U
Japan
383
National Chung Cheng U
Taiwan China
384
Hong Kong U S&T
Hong Kong China
387
National Cheng Chi U
Taiwan China
391
U Technology, Sydney
Australia
394
Kasetsart U
Thailand
418
Zhejiang U
China
425
City U of Hong Kong
Hong Kong China
435
Nanyang U Technology
Singapore
442
La Trobe U
Australia
453
Indian Institute of T Bombay
India
455
Victoria U Wellington
New Zealand
464
Korea U
Korea
468
Fudan U
China
477
Hong Kong Polytechnic U
Hong Kong China
482
Tamkang U
Taiwan China
491
Source: webometrics 2009
34 Table 3. Asia-Pacific universities in the Leiden ranking for ‘brute force’ in citation (citation data controlled for field of study but not institutional size), world top 250, 2003-2007 University
Nation
Position
U Tokyo
Japan
10
Kyoto U
Japan
27
Osaka U
Japan
36
Tohoku U
Japan
45
Seoul National U
Korea
57
National U of Singapore
Singapore
63
U Melbourne
Australia
70
U Sydney
Australia
72
U Queensland
Australia
88
National Taiwan U
Taiwan China
110
U Hong Kong
Hong Kong China
114
Nagoya U
Japan
119
Kyushu U
Japan
120
U New South Wales
Australia
125
Tokyo Institute of Technology
Japan
128
Tsinghua U
China
136
Australian National U
Australia
141
Peking U
China
145
Hokkaido U
Japan
146
Monash U
Australia
157
Yonsei U
Korea
159
Zheijang U
China
166
U Western Australia
Australia
193
Nanyang U Technology
Singapore
194
U Science and Technology China
China
195
Korean Advanced Institute of S&T
Korea
199
Shanghai Jiao Tong U
China
202
U Tsukuba
Japan
206
Korea U
Korea
216
National Chen Kung U
Taiwan China
226
Nanjing U
China
230
35 U Auckland
New Zealand
232
Hiroshima U
Japan
233
Fudan U
China
234
U Adelaide
Australia
236
Keio U
Japan
239
Chiba U
Japan
241
Okayama U
Japan
244
Hanyang U
Korea
245
Jilin U
China
248
Shandon U
China
250
Source: CWTS 2009
36 Table 4. Growth in the annual number of published science and technology papers*, Asia-Pacific countries, 1995-2005 Nation
1995
2005
Average annual change 1995-2005 %
Japan
47,068
55,471
1.7
China
9061
41,596
16.5
Korea
3803
16,396
15.7
13,125
15,957
2.0
India
9370
14,608
4.5
Taiwan China
4759
10,841
8.6
Singapore
1141
3609
12.2
New Zealand
2442
2983
2.0
Thailand
340
1249
13.9
Malaysia
366
615
5.3
Pakistan
313
492
4.6
Vietnam
103
221
7.9
Indonesia
129
205
4.7
Bangladesh
162
193
1.8
Philippines
145
178
2.1
Sri Lanka
85
136
4.7
all others in Asia**
76
152
7.2
Australia
* includes social science. ** Does not include Papua New Guinea and Pacific Islands. Source: NSB 2009.
