Universities from Australia and New Zealand in the 2015 edition of the Shanghai ranking

DC Technical Report 02/2015 Universities from Australia and New Zealand in the 2015 edition of the Shanghai ranking D. Docampo L. Cram October 24, 2015. Abstract The emergence of international academic rankings is one of the most interesting phenomena in the field of comparative analysis of higher education. The growing influence of the Shanghai ranking led its many critics to show strong reluctance in using it as a source of analysis and improvement, mainly because it was generally thought that its results were not reproducible. Once we have found a way to accurately replicate the results of the ranking, we are in a position to shed light into the performance of whole Higher Education systems. This technical report presents the results of Australian and New Zealand universities in the 2015 edition of the Shanghai ranking. Keywords Academic rankings Shanghai arwu world class universities Australian universities Australia Australian Higher Education System New Zealand universities New Zealand New Zealand Higher Education System 1 Introduction The Academic Ranking of World Universities (ARWU) a.k.a the Shanghai Ranking, evaluates the research performance of academic institutions on the basis of numerical measures related to individual outstanding achievements and institutional research throughput. The accessibility of the sources of the raw data and the fact that the hierarchy of universities generated by ARWU roughly aligns with perceptions of the historical and recent performance of elite research universities have contributed to its acceptance and success (Docampo and Cram, 2014). A first hand account of the Shanghai ranking indicators can be found in Liu and Cheng (2005), and is summarized in Section 2 following Docampo (2013). A reliable account of the ranking procedures can be found in Docampo and Cram (2014). For the sake of clarity, a summary of the procedure is also reproduced in section 3. Domingo Docampo Universidade de Vigo, Atlantic Research Center for Information and Communication Technologies; Campus Universitario, 36310 Vigo, Spain. E-mail: ddocampo@uvigo.es On sabatical at Charles Darwin University, Northern Institute, Ellengowan Drive, Brinkin NT 0909 Australia. E-mail: ddocampo@cdu.edu.au Lawrence Cram Research School of Physics and Engineering, Australian National University, Acton ACT 0200, Australia. E-mail: Lawrence.Cram@anu.edu.au Charles Darwin University, Northern Institute, Ellengowan Drive, Brinkin NT 0909 E-mail: Lawrence.Cram@cdu.edu.au

2 This report analyzes the performance of Higher Education institutions from Australia and New Zealand on the indicators measured by the Shanghai ranking (2015 edition). We have not included three institutions with very small publication counts: Avondale College, Melbourne College of Divinity and the Batchelor Institute of Indigenous Tertiary Education. To collect the necessary data for the computation of the ARWU raw scores, we have checked the electronic sources shown in Section 4. The list of special affiliation names and Web of Knowledge corresponding clues are shown in Section 5. Section 6 shows the procedure for the computation of the ARWU indicators. It is divided into two subsections, the first one dealing with the basic five indicators and the second one explaining how to compute the composed indicator (PCP). Finally, we present in Section 7 the results of 47 universities from Australia and New Zealand on the Shanghai ranking indicators. Data for the 47 universities under analysis have been estimated using the procedures described in Section 6. 2 ARWU ranking ARWU ranks universities on six indicators of academic performance. Individual indicators Alumni Total number of graduates from an institution winning Nobel Prizes or Fields Medals in Mathematics. Award Total number of the staff working at an institution at the time of winning Nobel prizes in the sciences, or Fields Medals in Mathematics. HiCi An equally weighted combination of two sub-indicators: old HiCi and new Hici, for the Highly cited researchers listed in the 2014 and 2001 version of Thompson Reuters Highly Cited Researchers, respectively 1. For ARWU 2015 the score on the old HiCi was the ARWU 2013 score. The highlycited.com web site indicates that highly cited researchers may change their affiliations monthly by changing their ResearcherID affiliation list. Collective indicators N&S Total number of articles published in Science and Nature in the past five years. PUB Total number of articles indexed by Science Citation Index-Expanded and Social Science Citation Index in the previous year. PCP Total scores of the previous five indicators divided by the number of full-time equivalent academic staff. 3 ARWU ranking methodology ARWU ranks universities individually or into bands by sorting on the total score, i.e. the linearly weighted sum of 6 indicator scores derived from the corresponding raw data by transformations that have been calibrated and explained by Docampo (2013). To produce the annual Shanghai ranking report the following steps are required: 1 http://highlycited.com/

3 1. Assemble new raw data Scan the relevant data sources (see Section 4) for updated information on new Nobel prize winners (every year) and Fields medalists (every four years), new awardees (expected in 2015) and revised affiliations of the current list of HCR for Thompson ISI Highly Cited researchers, and the institutional details of Nature & Science publications and ISI indexed publications in the prior year. Do your best to obtain the institutional FTE (full-time equivalent) faculty numbers used in the calculation of the PCP (per-capita performance) indicator. 2. Assess and determine exceptions Once per decade, rescale indicators for historical Nobel prize winners and Fields medalists according to the decadal aging procedure. Allocate institutions specialized in the humanities and the social sciences to the class that uses special weights to exclude Nature & Science publications. Decide which entire countries and which special institutions will be excluded from the determination of PCP because the relevant values of FTE have not been found. 3. Combine raw data and apply scaling Sum and/or average raw data over the relevant time windows according to the published algorithms. For every indicator other than PCP, multiply each value of the processed raw data by a fixed scaling factor so that Harvard University has a scaled raw score of 10000. Calculate an intermediate quantity for PCP by dividing the weighted sum of the scaled raw scores by the FTE for the California Institute of Technology, and apply a scaling factor so that this intermediate quantity for CalTech is 10000. 4. Compress the scaled raw data For each indicator, including PCP, compress the dynamic range of the scaled raw data by taking its square root to form the indicator score. 5. Calculate the total score and determine ranking/banding Combine the indicator scores using the relevant indicator weights, and linearly rescale so that the total score for Harvard University is 100. Rank institutions by total score, and determine for publication the ranking sequence, the membership of bands, and the excluded institutions. 4 Electronic sources Data were gathered from the following Electronic Sources: Nobel Prize Laureates available at http://nobelprize.org/ Data on Field Medalists available at http://en.wikipedia.org/wiki/fields Medal Data on Highly Cited Authors available at http://highlycited.com/ Data on scientific production available at http://www.webofknowledge.com. Preprint copies of published articles related to this technical report are available at https://www.researchgate.net/profile/lawrence Cram/contributions/ https://www.researchgate.net/profile/daniel Egret/contributions/ https://www.researchgate.net/profile/domingo Docampo/contributions/ 5 Affiliation names We have conducted electronic searches using the organizations enhanced (og) names feature of the Web of Knowledge. According to Thomson Reuters (Thomson Reuters,

4 2013), og names precisely identify research published from a specific organization using the Organization - Enhanced searching to quantify an organizations output including naming variants. We used those og identifiers with most universities, but made special calls in some cases, as shown in Table 1. It is not unlikely that some disambiguation problems with affiliations may still persist, so we warmly invite comments on any apparent errors or uncertainties. Web of Knowledge call oo=australian catholic univ og=(flinders university south australia or flinders univ south australia) oo=monash univ oo=(rmit univ or rmit or rmit univ melbourne) oo=swinburne univ technol og=(university of canterbury or univ canterbury) og=(university of melbourne or univ melbourne or royal children s hospital melbourne) og=(university of notre dame australia or notre dame univ) og=(university of queensland or univ queensland or queensland ctr mental hlth res) og=(university of sydney or univ sydney or sydney med sch) oo=univ tasmania oo=univ technol sydney oo=(univ western australia or uwa or uwa ocean inst) oo=victoria univ and ad=melbourne Table 1: Special cases : WOK organization (oo) or organization-enhanced (og) names 6 Computation of the indicator scores Final scores depend on raw scores, specifically on their ratio: universities to the best performer institution. Hence, the first step is to evaluate those raw scores on the five non composed indicators: Alumni, Award, HICI, S&N and PUB. For a complete account of the computation of raw scores the reader is referred to Docampo (2013). 6.1 Computation of the five basic indicators For the computation of the non composed indicators (Alumni, Staff, HiCi, S&N, and PUB) we need the raw scores of the best performer. Harvard University achieves the maximum score on the five non composed indicators in the 2015 edition of ARWU. Harvard s (approximate in the case of the S&N and PUB indicators) raw scores are exhibited in Table 2. Let us now summarize the precise operations with the raw scores Alumni Award newhici oldhici S&N PUB 38 33.875 100 191 464 16860 Table 2: Harvard University raw scores in 2015 described in steps 4 and 5 of Section 3. Let H be the number of points (raw score) of Harvard on any of the five indicators, and X the number of points achieved by any other institution. Estimated scores are computed through the same formula 2 : X EST = 100 (1) H 2 In the case of the HiCi indicator the equation applies to both the old and new HCR counting separately.

5 Institution FTE Faculty ASL LLC FTE Australian Catholic University 141 159 300 Australian National University 559 321 880 Bond University 130 27 157 Central Queensland University 90 120 210 Charles Darwin University 46 59 105 Charles Sturt University 140 166 306 Curtin University of Technology 369 274 643 Deakin University 307 322 629 Edith Cowan University 113 161 274 Federation University Australia 48 57 105 Flinders University 250 198 448 Griffith University 428 367 795 James Cook University 200 198 398 La Trobe University 225 250 475 Macquarie University 317 225 542 Monash University 746 644 1390 Murdoch University 149 139 288 Queensland University of Technology 410 330 740 Royal Melbourne institute of Technology (RMIT) 300 357 657 Southern Cross University 76 91 167 Swinburne University of Technology 167 138 305 University of Adelaide 406 331 737 University of Canberra 124 126 250 University of Melbourne 917 527 1444 University of New England 121 110 231 University of New South Wales 793 724 1517 University of Newcastle, Australia 268 252 520 University of Notre Dame Australia 55 127 182 University of Queensland 739 516 1255 University of South Australia 211 317 528 University of Southern Queensland 106 108 214 University of Sydney 915 650 1565 University of Tasmania 220 244 464 University of Technology, Sydney 289 299 588 University of the Sunshine Coast 57 58 115 University of Western Australia 481 359 840 University of Western Sydney 275 273 548 University of Wollongong 299 228 527 Victoria University 132 138 270 Table 3: Full Time Equivalent Staff of Australian universities in ARWU 2015. Source: Australian Government, Department of Education. 6.2 PCP computation There is no easy way to access reliable data on equivalent full-time faculty for all the institutions listed in ARWU. However, in the case of Australian universities, there are public and reliable data published by the Department of Education. The number of Full Time Equivalent Academic Staff used in ARWU for Australian universities is computed as the aggregate number of Full Time Equivalent Faculty at the levels above Senior Lecturer and Lecturer (Level C). For the 2015 edition ARWU has apparently made use of FTE data from the following document: Selected Higher Education Statistics Staff 2013 Full-time Equivalence (AUSTRALIAN-GOVERNMENT, 2014).

6 Data from the 39 Australian universities included in the analysis are shown in Table 3, where the acronyms of the three columns stand for: ASL: Full Time Equivalent number of Faculty above Senior Lecturer. LLC: Full Time Equivalent number of Faculty at Lecturer Level C. FTE: Full Time Academic Staff for the calculations of the ARWU data. FTE figures for New Zealand universities have been left unchanged from ARWU 2013 to ARWU 2015. As of the estimation of FTE values for universities not included in the ARWU 500 list we refer the reader to our previous report (Docampo and Cram, 2013). The FTE values are shown in Table 4. Institution year Academic Staff FTE Staff Massey University 2012 1, 072 673 The University of Auckland 2011 2, 050 929 University of Canterbury 2012 690 402 University of Otago 2012 1, 162 406 Victoria University of Wellington 2012 817 463 Auckland University of Technology 2011 1, 070 528 Lincoln University 2012 235 116 University of Waikato 2012 637 314 Table 4: Institutional figures for FTE academic and total staff: universities from New Zealand. Source: Annual reports of New Zealand universities Now, to get the PCP values for all the universities included in the analysis, both from Australia and New Zealand, we first compute the weighted sum of the squares of the estimated scores. The procedure has changed due to the introduction of the old and new Hici sub-indicators, as documented in Docampo et al (2015). In the 2014 and 2015 editions of ARWU, the weighted sum is evaluated through Equation 2; let s call that value WSS. WSS = 0.1 ( Alumni 2 + newhici 2 + oldhici 2) + 0.2 ( Award 2 + N&S 2 + PUB 2) (2) Let s call WSSCT the value of the squared sums for Caltech, the highest score in the indicator PCP. Let FTECT be the Full Time Equivalent Staff of Caltech. To estimate the PCP indicator of the university X, with a Full Academic Staff of FTEX and weighted scores sum of WSSX, the following operation will be carried out: PCP = 100 WSSX FTEX WSSCT FTECT = 100 FTECT WSSX WSSCT FTEX (3) To compute formula 3 we introduce the value of 278 for the FTE Academic Staff of Caltech. In 2015, WSSCT 2657.4, hence we have FTECT W SSX = 0.3236 PCP = 32.36 WSSCT F T EX (4)

7 7 Results We show in Figure 1 the results of the 47 institutions under analysis 3. It is perhaps worth pointing out that the entrance score in ARWU 2015 was close to 9.5. We show in Figure 2 the the 47 institutions ranked by PCP. References AUSTRALIAN-GOVERNMENT (2014) Selected Higher Education Statistics Staff 2013 Full-time Equivalences. TRIM Reference D14/199109, URL http://docs.education.gov.au/documents/selected-higher-education-statistics-staff- 2013-full-time-equivalence, downloaded from the Department of Education and Training server on August 19th 2015. Docampo D (2013) Reproducibility of the Shanghai academic ranking of world universities results. Scientometrics 94(2):567 587 Docampo D, Cram L (2013) Universities from Australia and New Zealand and the 2013 edition of the Shanghai ranking. ATLANTIC Technical Report 2/2013, URL https://www.researchgate.net/publication/259369356 Docampo D, Cram L (2014) On the Internal Dynamics of the Shanghai ranking. Scientometrics 98(2):1347 1366 Docampo D, Egret D, Cram L (2015) The effect of university mergers on the Shanghai ranking. Scientometrics 104(1):175 191 Liu NC, Cheng Y (2005) Academic ranking of world universities: Methodologies and problems. Higher Education in Europe, 30(2):127 136 Thomson Reuters (2013) Web of knowledge v5.9 release notes. URL http://wokinfo.com/media/pdf/webofknowledge5-9rn.pdf 3 To test the accuracy of our estimation we provide in the table our figures for the universities in ARWU 500, so the reader may check that the errors are almost negligible

8 ranking ARWU ARWU INDICATORS local ranking score Universities world 2013 2015 Fig. 1: Universities from Australia alu awd and newhnew oldhzealand hici S&N ranked PUB by pcptotal ARWU2013 score 2015 RDIF 2013 2015 SDIF 44 yes yes Univ Melbourne 17.0 13.3 33.2 24.0 28.6 25.3 66.9 30.2 32.3 1444 1 1 0 30.2 32.3 2.1 77 yes yes Australian Natl Univ 13.6 19.2 17.3 32.3 24.8 20.1 45.1 29.2 26.7 880 2 2 0 28.9 26.7-2.2 77 yes yes Univ Queensland 12.6 0.0 22.4 21.7 22.0 24.0 63.2 29.3 26.7 1255 3 2 1 25.5 26.7 1.2 87 yes yes Univ Western Australia 13.6 14.1 22.4 25.8 24.1 14.5 47.5 28.9 24.9 840 4 4 0 24.9 24.9 0.0 101-125 yes yes Monash Univ 0.0 0.0 22.4 14.5 18.4 22.6 59.1 25.6 23.1 1390 7 5 2 20.6 23.1 2.5 101-125 yes yes Univ Sydney 14.5 0.0 0.0 19.1 9.6 18.2 64.7 25.4 23.0 1565 5 6-1 24.7 23.0-1.7 101-125 yes yes Univ New South Wales 0.0 0.0 20.0 20.4 20.2 17.5 58.5 23.9 22.1 1517 6 7-1 20.9 22.1 1.2 151-200 yes yes Univ Adelaide 14.5 0.0 22.4 10.2 16.3 12.8 42.0 25.8 18.7 737 9 8 1 16.2 18.7 2.5 201-300 yes yes Univ Auckland 13.6 0.0 10.0 10.2 10.1 11.9 41.0 21.3 16.5 931 8 9-1 16.4 16.5 0.1 201-300 yes yes Macquarie Univ 0.0 0.0 20.0 16.2 18.1 13.1 33.6 25.1 15.8 542 11 10 1 14.3 15.8 1.5 201-300 yes yes Univ Wollongong 0.0 0.0 24.5 10.2 17.4 9.2 31.7 23.9 14.4 527 16 11 5 11.9 14.4 2.5 201-300 yes yes Univ Otago 0.0 0.0 10.0 14.5 12.2 10.1 34.1 27.1 14.3 405 10 12-2 15.0 14.3-0.7 201-300 yes yes Curtin Univ 0.0 0.0 17.3 0.0 8.7 12.1 37.1 23.3 14.2 643 20 13 7 10.6 14.2 3.6 301-400 yes yes Univ Tasmania 0.0 0.0 10.0 10.2 10.1 15.1 28.9 22.9 13.4 464 12 14-2 12.7 13.4 0.7 301-400 yes yes James Cook Univ 0.0 0.0 10.0 10.2 10.1 15.4 27.4 24.0 13.3 398 13 15-2 12.6 13.3 0.7 301-400 yes yes Univ Newcastle 0.0 0.0 10.0 12.2 11.1 5.4 33.0 22.4 12.4 520 15 16-1 12.1 12.4 0.3 301-400 yes yes Griffith Univ 0.0 0.0 0.0 7.2 3.6 8.2 37.1 19.7 12.0 795 17 17 0 11.7 12.0 0.3 301-400 yes yes Flinders Univ 15.4 0.0 0.0 10.2 5.1 5.1 29.1 22.1 11.9 448 14 18-4 12.5 11.9-0.6 301-400 yes yes Univ Technol Sydney 0.0 0.0 14.1 14.5 14.3 3.9 28.5 19.2 11.5 588 20 19 1 10.6 11.5 0.9 301-400 yes yes Swinburne Univ Tech 0.0 0.0 10.0 12.5 11.3 10.7 22.3 22.6 11.4 305 18 20-2 11.5 11.4-0.1 301-400 no yes Deakin Univ 0.0 0.0 0.0 0.0 0.0 8.6 35.4 21.0 11.2 629 25 21 4 9.2 11.2 2.0 401-500 no yes Queensland Univ Tech 0.0 0.0 0.0 0.0 0.0 3.3 34.6 18.5 9.7 740 26 22 4 9.0 9.7 0.7 501-600 yes no La Trobe Univ 0.0 0.0 0.0 7.2 3.6 4.8 27.9 19.1 9.4 475 23 23 0 9.6 9.4-0.2 501-600 yes no Univ Canterbury 0.0 0.0 0.0 7.2 3.6 8.9 23.8 18.7 9.3 401 19 24-5 10.7 9.3-1.4 501-600 no no Univ New England 0.0 0.0 10.0 7.2 8.6 5.7 19.5 21.1 9.1 231 30 25 5 6.4 9.1 2.7 501-600 yes no Victoria Univ Wellington 11.5 0.0 0.0 0.0 0.0 6.3 23.6 17.4 9.1 458 24 25-1 9.4 9.1-0.3 501-600 yes no Massey Univ 0.0 0.0 0.0 10.2 5.1 5.9 25.4 15.1 9.0 669 22 27-5 9.7 9.0-0.7 501-600 no no Univ Western Sydney 0.0 0.0 0.0 0.0 0.0 6.2 27.8 17.6 8.8 548 28 28 0 7.9 8.8 0.9 501-600 no no Univ South Australia 0.0 0.0 0.0 0.0 0.0 3.1 29.9 18.9 8.7 528 27 29-2 8.1 8.7 0.6 601-800 no no Murdoch Univ 0.0 0.0 0.0 7.2 3.6 4.9 20.0 18.1 7.7 288 31 30 1 6.3 7.7 1.4 601-800 no no RMIT 0.0 0.0 0.0 0.0 0.0 0.0 27.0 15.2 7.1 657 32 31 1 6.2 7.1 0.9 601-800 no no Southern Cross Univ 0.0 0.0 0.0 7.2 3.6 2.5 16.6 19.7 6.7 167 36 32 4 4.9 6.7 1.8 801-1000 no no Charles Darwin Univ 0.0 0.0 0.0 0.0 0.0 2.5 16.1 23.0 6.2 105 35 33 2 5.2 6.2 1.0 801-1000 no no Univ Sunshine Coast 0.0 0.0 0.0 0.0 0.0 4.9 15.0 21.3 6.2 115 40 33 7 3.8 6.2 2.4 801-1000 no no Univ Waikato 0.0 0.0 0.0 10.2 5.1 0.0 17.4 15.2 6.2 320 29 33-4 7.1 6.2-0.9 801-1000 no no Charles Sturt Univ 0.0 0.0 0.0 0.0 0.0 2.3 18.7 15.6 5.9 306 33 36-3 5.7 5.9 0.2 801-1000 no no Univ Canberra 0.0 0.0 0.0 0.0 0.0 3.3 17.1 15.9 5.8 250 37 37 0 4.7 5.8 1.1 801-1000 no no Edith Cowan Univ 0.0 0.0 0.0 0.0 0.0 2.1 17.7 15.6 5.6 274 45 38 7 2.5 5.6 3.1 1001-1250 no no Victoria Univ Melbourne 0.0 0.0 0.0 0.0 0.0 0.0 18.1 15.9 5.3 270 33 39-6 5.7 5.3-0.4 1001-1250 no no Central Queensland Univ 0.0 0.0 10.0 0.0 5.0 0.0 12.9 14.7 5.2 210 44 40 4 2.7 5.2 2.5 1001-1250 no no Australian Catholic Univ 0.0 0.0 0.0 0.0 0.0 0.0 17.7 14.8 5.1 300 47 41 6 1.8 5.1 3.3 1001-1250 no no Lincoln Univ 0.0 0.0 10.0 0.0 5.0 1.5 11.9 12.5 5.0 261 42 42 0 3.3 5.0 1.7 1001-1250 no no Auckland Univ Tech 0.0 0.0 0.0 0.0 0.0 1.5 16.6 10.5 4.8 528 38 43-5 4.3 4.8 0.5 1001-1250 no no Fed Univ Australia 0.0 0.0 0.0 0.0 0.0 1.5 12.6 17.9 4.7 105 43 44-1 3.1 4.7 1.6 1001-1250 no no Bond Univ 0.0 0.0 0.0 0.0 0.0 3.3 11.4 13.7 4.4 157 41 45-4 3.5 4.4 0.9 1251-1500 no no Univ S Queensland 0.0 0.0 0.0 0.0 0.0 2.1 12.7 12.7 4.3 214 39 46-7 4.1 4.3 0.2 1501-2000 no no Univ Notre Dame 0.0 0.0 0.0 0.0 0.0 1.5 10.7 11.6 3.7 182 46 47-1 2.2 3.7 1.5 SCORE FTE

9 ranking ARWU ARWU INDICATORS pcp ranking pcp score Universities world 2013 Fig. 2015 2: Universities from Australiaalu andawd Newnewh Zealand oldhranked hici S&N by the PUBscore on the 2013 PCP 2015 indicator rdif 2013 2015 sdif 44 yes yes Univ Melbourne 17.0 13.3 33.2 24.0 28.6 25.3 66.9 30.2 1444 3 1 2 27.1 30.2 3.1 77 yes yes Univ Queensland 12.6 0.0 22.4 21.7 22.0 24.0 63.2 29.3 1255 5 2 3 26.5 29.3 2.8 77 yes yes Australian Natl Univ 13.6 19.2 17.3 32.3 24.8 20.1 45.1 29.2 880 1 3-2 29.3 29.2-0.1 87 yes yes Univ Western Australia 13.6 14.1 22.4 25.8 24.1 14.5 47.5 28.9 840 2 4-2 27.3 28.9 1.6 201-300 yes yes Univ Otago 0.0 0.0 10.0 14.5 12.2 10.1 34.1 27.1 405 4 5-1 26.6 27.1 0.5 151-200 yes yes Univ Adelaide 14.5 0.0 22.4 10.2 16.3 12.8 42.0 25.8 737 7 6 1 22.4 25.8 3.4 101-125 yes yes Monash Univ 0.0 0.0 22.4 14.5 18.4 22.6 59.1 25.6 1390 8 7 1 22.1 25.6 3.5 101-125 yes yes Univ Sydney 14.5 0.0 0.0 19.1 9.6 18.2 64.7 25.4 1565 6 8-2 23.9 25.4 1.5 201-300 yes yes Macquarie Univ 0.0 0.0 20.0 16.2 18.1 13.1 33.6 25.1 542 10 9 1 21.6 25.1 3.5 301-400 yes yes James Cook Univ 0.0 0.0 10.0 10.2 10.1 15.4 27.4 24.0 398 9 10-1 21.7 24.0 2.3 201-300 yes yes Univ Wollongong 0.0 0.0 24.5 10.2 17.4 9.2 31.7 23.9 527 18 11 7 19.4 23.9 4.5 101-125 yes yes Univ New South Wales 0.0 0.0 20.0 20.4 20.2 17.5 58.5 23.9 1517 11 11 0 21.5 23.9 2.4 201-300 yes yes Curtin Univ 0.0 0.0 17.3 0.0 8.7 12.1 37.1 23.3 643 19 13 6 17.8 23.3 5.5 801-1000 no no Charles Darwin Univ 0.0 0.0 0.0 0.0 0.0 2.5 16.1 23.0 105 13 14-1 21.0 23.0 2.0 301-400 yes yes Univ Tasmania 0.0 0.0 10.0 10.2 10.1 15.1 28.9 22.9 464 14 15-1 20.4 22.9 2.5 301-400 yes yes Swinburne Univ Tech 0.0 0.0 10.0 12.5 11.3 10.7 22.3 22.6 305 12 16-4 21.4 22.6 1.2 301-400 yes yes Univ Newcastle 0.0 0.0 10.0 12.2 11.1 5.4 33.0 22.4 520 15 17-2 20.0 22.4 2.4 301-400 yes yes Flinders Univ 15.4 0.0 0.0 10.2 5.1 5.1 29.1 22.1 448 13 18-5 20.5 22.1 1.6 201-300 yes yes Univ Auckland 13.6 0.0 10.0 10.2 10.1 11.9 41.0 21.3 931 16 19-3 19.9 21.3 1.4 801-1000 no no Univ Sunshine Coast 0.0 0.0 0.0 0.0 0.0 4.9 15.0 21.3 115 31 19 12 15.0 21.3 6.3 501-600 no no Univ New England 0.0 0.0 10.0 7.2 8.6 5.7 19.5 21.1 231 26 21 5 16.7 21.1 4.4 301-400 no yes Deakin Univ 0.0 0.0 0.0 0.0 0.0 8.6 35.4 21.0 629 23 22 1 17.1 21.0 3.9 301-400 yes yes Griffith Univ 0.0 0.0 0.0 7.2 3.6 8.2 37.1 19.7 795 20 23-3 17.5 19.7 2.2 601-800 no no Southern Cross Univ 0.0 0.0 0.0 7.2 3.6 2.5 16.6 19.7 167 28 23 5 15.8 19.7 3.9 301-400 yes yes Univ Technol Sydney 0.0 0.0 14.1 14.5 14.3 3.9 28.5 19.2 588 21 25-4 17.2 19.2 2.0 501-600 yes no La Trobe Univ 0.0 0.0 0.0 7.2 3.6 4.8 27.9 19.1 475 23 26-3 17.1 19.1 2.0 501-600 no no Univ South Australia 0.0 0.0 0.0 0.0 0.0 3.1 29.9 18.9 528 26 27-1 16.7 18.9 2.2 501-600 yes no Univ Canterbury 0.0 0.0 0.0 7.2 3.6 8.9 23.8 18.7 401 17 28-11 19.5 18.7-0.8 401-500 no yes Queensland Univ Tech 0.0 0.0 0.0 0.0 0.0 3.3 34.6 18.5 740 21 29-8 17.2 18.5 1.3 601-800 no no Murdoch Univ 0.0 0.0 0.0 7.2 3.6 4.9 20.0 18.1 288 30 30 0 15.5 18.1 2.6 1001-1250 no no Fed Univ Australia 0.0 0.0 0.0 0.0 0.0 1.5 12.6 17.9 105 33 31 2 12.8 17.9 5.1 501-600 no no Univ Western Sydney 0.0 0.0 0.0 0.0 0.0 6.2 27.8 17.6 548 29 32-3 15.6 17.6 2.0 501-600 yes no Victoria Univ Wellington 11.5 0.0 0.0 0.0 0.0 6.3 23.6 17.4 458 25 33-8 16.9 17.4 0.5 1001-1250 no no Victoria Univ Melbourne 0.0 0.0 0.0 0.0 0.0 0.0 18.1 15.9 270 35 34 1 13.3 15.9 2.6 801-1000 no no Univ Canberra 0.0 0.0 0.0 0.0 0.0 3.3 17.1 15.9 250 38 35 3 12.7 15.9 3.3 801-1000 no no Charles Sturt Univ 0.0 0.0 0.0 0.0 0.0 2.3 18.7 15.6 306 34 36-2 14.0 15.6 1.6 801-1000 no no Edith Cowan Univ 0.0 0.0 0.0 0.0 0.0 2.1 17.7 15.6 274 45 36 9 7.1 15.6 8.5 801-1000 no no Univ Waikato 0.0 0.0 0.0 10.2 5.1 0.0 17.4 15.2 320 35 38-3 13.3 15.2 2.0 601-800 no no RMIT 0.0 0.0 0.0 0.0 0.0 0.0 27.0 15.2 657 37 38-1 12.8 15.2 2.5 501-600 yes no Massey Univ 0.0 0.0 0.0 10.2 5.1 5.9 25.4 15.1 669 32 40-8 14.6 15.1 0.5 1001-1250 no no Australian Catholic Univ 0.0 0.0 0.0 0.0 0.0 0.0 17.7 14.8 300 47 41 6 5.1 14.8 9.6 1001-1250 no no Central Queensland Univ 0.0 0.0 10.0 0.0 5.0 0.0 12.9 14.7 210 42 42 0 8.3 14.7 6.4 1001-1250 no no Bond Univ 0.0 0.0 0.0 0.0 0.0 3.3 11.4 13.7 157 40 43-3 11.6 13.7 2.1 1251-1500 no no Univ S Queensland 0.0 0.0 0.0 0.0 0.0 2.1 12.7 12.7 214 39 44-5 11.9 12.7 0.9 1001-1250 no no Lincoln Univ 0.0 0.0 10.0 0.0 5.0 1.5 11.9 12.5 261 44 45-1 7.9 12.5 4.6 1501-2000 no no Univ Notre Dame 0.0 0.0 0.0 0.0 0.0 1.5 10.7 11.6 182 46 46 0 6.8 11.6 4.8 1001-1250 no no Auckland Univ Tech 0.0 0.0 0.0 0.0 0.0 1.5 16.6 10.5 528 41 47-6 10.3 10.5 0.2 PCP FTE