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Table 1: Categories of ASA membership, showing the number of members (N) in each category and the fraction of each that were excluded (X) from the subsequent analysis due to name confusion (see Section 2). We ignore the extra categories of Associate Society member (i.e. persons who are members of other learned societies that are likely to not possess Ph.D.’s in astronomy) and corporate members. It is important to note that individual researchers can belong to multiple categories; e.g. retired, overseas fellows.

Category N X Notes M 262 0.10 Member: Full professional member with a Ph.D. in astronomy or related discipline. F 81 0.10 Fellow: Senior members of the community with potentially decades of experience. S 164 0.09 Student: Post-graduate students studying toward Ph.D.’s in astronomy. H 15 0.00 Honourary: Elected by the ASA council for distinguished contributions. R 54 0.11 Retired. O 56 0.10 Overseas. A 14 0.00 Associate Members: Educators, communicators and amateur astronomers lacking a Ph.D.

searchers, including attempting common substitutions for first names; e.g., ‘Bill’ for ‘William’, etc. However, for the very common surnames (e.g. Smith), this is not always possible. Therefore, the subsequent analy- sis in this work does not include any names for which we could not adequately differentiate a single individ- ual in the literature in a reasonable amount of time. This affects ∼10% of the membership list and is la- belled X in Table 1. We caution that the subsequent analysis should therefore be regarded as incomplete: the inclusion of these names could increase or decrease the relative rankings of individuals within the ASA membership. We also note that we make no attempt to exclude self-citations in our analysis (e.g. Pimbblet 2011). Finally, it may be the case that some of the categories may not be up-to-date due to (e.g.) student members gaining their Ph.D.’s and either not upgrad- ing to full membership status immediately or the list itself not being updated immediately.

3 h-index by ASA Member- ship Category

This simplest point of departure for the h-index anal- ysis is to pull out the top ten: those people who could rightly be called academic giants in their own right in the community. To do this, we simply rank all profes- sional members who are not based overseas (i.e. cat- egories M+F+S+H+R; Table 1). This top ten list is presented in Table 2. Figure 1: Histogram of h-index for all ASA mem- Although we refrain from commenting on individ- bers, excluding those for whom name confusion uals in this list, it is instructive to compare it to Conti et al.’s (2011) list. The h-index values for the top could not be resolved. ten AAS members is much higher than the Australian (94 Redshift Survey (e.g. Colless et al. 2001). Moreover, since the award of a Ph.D. the majority of the listed researchers in Table 2 also feature in Thomson Reuters’ ISI’s highly cited list (isi- highlycited.com) for space science. 4 h-index by Years Since Ph.D. Award h Table 2: Top 10 -index for Australian Astronomy, Even the award year of a Ph.D. must be regarded with excluding overseas professionals. healthy suspicion as a metric for performance relative Rank Name h to opportunity. This is especially true for early-career =1 KenFREEMAN 77 researchers who may complete their Ph.D. whilst un- =1 JeremyMOULD 77 dertaking their first post-doctoral placement and for 3 KarlGLAZEBROOK 71 the many researchers who have had significant time 4 Dick MANCHESTER 68 away from the profession; the present author included. 5 Michael DOPITA 64 To determine the award date of the Ph.D., we use 6 WarrickCOUCH 61 the results from ADS where available. If the Ph.D. 7 MatthewCOLLESS 56 is not listed in ADS, then we use the date of the sec- ond first-author refereed publication by the member 8 BrianSCHMIDT 54 as a compromise proxy for this date, given the dis- =9 MikeBESSELL 53 tribution of the S sample in Table 3. This date was =9 Joss BLAND-HAWTHORN 53 determined for all ASA members in the M+F+R-O category. Where no date could be determined by ei- ther method, the member was simply removed from the list. This may have the effect of meaning that the But what of the rest of the community? In Figure 1 percentiles for this sample are upper limits as we have we display a histogram of h-index for all ASA mem- missed doctoral researchers who have few first author bers. This graph is dominated by those members hav- publications. We present the percentiles of this dis- ing a zero h-index or slightly above, much as the AAS tribution in Table 4. The results show a fairly steady community is (Conti et al. 2011). The vast majority of progression as one increases in seniority from Ph.D. these members are student members, many of whom award date without any obvious discrepancies, as may are likely to not have published. Even if they have be expected. However, one comment to be made is published, the duration of the Ph.D. may mean that that there seems many less young professionals in the sufficient time has not elapsed to gain large numbers samples than there perhaps should be (given the num- of citations and that only the very exceptional papers bers in more senior years). This tentatively suggests produced by students garner large number of citations that new recruits to Australian Astronomy may not be immediately. Clearly students in present-day collabo- joining the ASA immediately. rations such as WiggleZ (Drinkwater et al. 2010) will Further, not all areas and sub-disciplines of sci- benefit from this effect much in the same way as SDSS ence and astronomy may be equal. Those researchers members receive a boost. involved in (e.g.) instrumentation may have a very dif- To analyse the content of Figure 1 in a more in- ferent h-index distribution to those researching obser- depth manner, we now create sub-samples of the ASA vational cosmology (particularly those in larger-sized membership according to grade and determine vari- consortia). ous percentiles of the h-index distribution. These per- centiles are presented in Table 3. We do not present results for individual categories H, O, R and A due to 5 Conclusions low numbers. This can be seen in the relatively tiny difference between the percentiles quoted for M+F+R- This work has presented an analysis of the h-index dis- O versus M+F-R-O samples in Table 3. tributions for present members of the ASA. As well as We start by discussing the student membership re- deriving a top ten (Table 2), we have presented the sult. At the upper echelons, students appear to have percentiles for various sub-samples of the ASA’s mem- an h-index comparable of junior professionals. But a bership, including student statistics (Table 3). We careful analysis of the membership list reveals that this have also attempted to analyse the distribution rela- is exactly what these students are: junior profession- tive to opportunity by detailing the percentiles by time als who should be in the M category. We argue that elapsed since Ph.D. award date (Table 4). anything above the 90th percentile for the S category Clearly the h-index is a crude estimator of the should be regarded with suspicion. value of a researcher and should not be used in iso- 4 Publications of the Astronomical Society of Australia

Table 3: Percentiles of h-index distribution by ASA membership grade. N gives the total number of members for each row. Category N Percentile 25 50 75 90 95 97.5 99 M 235 6.0 12.0 21.0 32.5 43.0 47.8 52.4 F 73 21.0 30.0 39.8 50.0 59.2 69.8 75.4 S 149 0.0 0.0 2.0 4.0 5.0 6.7 9.5 M+F-R-O 227 7.0 15.0 28.0 41.0 45.0 53.0 63.7 M+F+R-O 266 6.0 15.0 28.0 40.0 45.4 53.3 68.8 M+F+S-R-O 374 1.0 5.0 19.0 33.6 42.3 46.7 59.7

Table 4: Percentiles of h-index distribution by years since Ph.D. award (explicitly: 2011 minus the award date). Only members in M+R+F-O categories are included. N gives the total number of members for each row. Years since N Percentile Ph.D.award 25 50 75 90 95 97.5 99 0–5 32 5.0 6.0 9.0 10.0 13.2 15.8 16.3 6–10 42 8.5 14.0 19.0 22.0 25.0 27.8 29.7 11–20 74 12.5 19.0 28.5 39.6 43.4 53.1 58.4 >20 94 12.0 25.0 38.0 47.2 55.1 62.9 77.0

lation to other metrics, even if it is a good predictor of Blustin, A. 2007, Astronomy & Geophysics, 48, 6.32 future productivity (Hirsch 2007). It will be instruc- tive to re-visit this analysis in future years or decades Bornmann, L., Mutz, R., Daniel, H.-D. 2008, Journal to determine how the field has changed. of the American Society for Information Science and We terminate this work with a caveat emptor: there Technology, 59, 830 are known deficiencies in this analysis such as numer- ous missing persons (who are not ASA members) whose Colless, M., et al. 2001, MNRAS, 328, 1039 statistics may alter the results presented. We have Conti A., Lowe S., Accomazzi A., DiM- tried to be up-front with various caveats throughout ilia G. 2011, AAS, 217, #145.01 (see this work, but there may yet be unknown unknowns http://dl.dropbox.com/u/473509/Astro-HR.pdf) present as well. Further, there may exist transcription errors that went un-detected during the data assem- Drinkwater, M. J., et al. 2010, MNRAS, 401, 1429 bly stage. However, as far as possible, we believe the numbers quoted in this work are accurate. Egghe, L. 2006, Scientometrics, 69, 131

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