Demographic Summary
|
2012 PRAC Report
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November 2016
|
Total Number of AEs
|
147
|
135
|
Average AE Workload, papers
|
4.99
|
7.58
|
Organizational Diversity
|
|
Academia
|
51%
|
63.4%
|
Industrial
|
47.6%
|
36.6%
|
Government
|
1.4%
|
See note below
|
Regional Diversity (%) of AEs
|
|
1 through 6
|
57.9%
|
47.8%
|
7
|
8.3%
|
6.7%
|
8
|
20.7%
|
23.9%
|
9
|
1.4%
|
3.0%
|
10
|
11.7%
|
19.4%
|
Regional Diversity (%) of Membership
|
|
1 through 6
|
54%
|
47.9%
|
7
|
7.5%
|
5.6%
|
8
|
16.8%
|
17.8%
|
9
|
8.3%
|
8.8%
|
10
|
13%
|
19.9%
|
Gender Diversity (%)
|
|
Male
|
95.20%
|
97.0%
|
Female
|
4.80%
|
3.0%
|
|
|
|
This team of AEs reflects significant geographic and institutional diversity. It also includes significant representation from the major geographic constituencies in IAS. And in comparing the most recent statistics with those from our 2012 PRAC report, there is a noticeable shift toward a more global team.
Within IAS we have people who are employed by government regulatory agencies, government laboratories and various military organizations. There is a significant difference between working in a research laboratory and working on regulatory policy, and to generically group both sets under the heading ‘Government’ doesn’t make sense. Furthermore, many (and perhaps most) government-owned laboratories are actually managed by private industrial concerns. Hence, we have categorized AEs who work for government-owned laboratories as ‘industrial’, and AEs who work for government regulatory agencies as ‘government’
In our 2012 review, several members of the PRAC questioned the number of IAS Associate Editors. Our response was, and continues to be, that the very broad range of technical interests of the Society requires that we have Associate Editors who reflect the range of technologies covered by our constituents and the selection of topics addressed in the papers that come to us for review. As a consequence, we believe that our situation demands that we have more Associate Editors than would be the case in a Society that focuses on a narrower slice of technology.
However, we recognize the concern raised by the PRAC that the combination of a large number of Associate Editors and a large number of authors could suggest the possibility of collusion between authors and Associate Editors, eg, situations where an author of paper A is coincidentally the Associate Editor responsible for a different paper (B) whose list of authors includes the Associate Editor responsible for paper A, and the two individuals reach a quid-pro-quo agreement to assure that both papers are approved for publication. There is no evidence that this kind of improper behavior has ever actually happened in IAS. But to address the perception of a potential problem, we have reduced the total number of Associate Editors at the same time that we have experienced a significant increase in the number of submissions, effectively resulting in a significant increase in the workload imposed on individual AEs. AEs are volunteers. Obviously, this is not a trend that we will be able to maintain without limit, and we anticipate that if submissions continue to increase, we may have to cap workload and expand the number of AEs.
IAS takes a number of steps to regularly refresh the population of AEs supporting our publication activities. Because we use ScholarOne Manuscripts as our peer review management tool, we have total control over who can actually access the tool as an AE and therefore who can function in that capacity. Our practice is that access to S1M by all AEs expires on 1 February of even-numbered years – that forces the internal discipline of periodically assessing each AE and deciding if he or she will continue for another term. Obviously, because we are a volunteer-based organization, we always reflect the interests of individual volunteers, and attempt to accommodate the wishes of AEs who feel that they have done their share and wish to retire. Likewise, we take into account the wishes of our Technical Committees to introduce new people to the process. At the same time, we are sensitive to the very real issue of ‘title collectors’ who readily volunteer to become AEs so they can list that honor on their resume, but then are less enthusiastic about actually doing the work.
We use two hard metrics to objectively evaluate the performance of individual AEs– the number of papers that the AE has handled, and the average time to first decision reported on the papers handled by that AE. These parameters are calculated for each AE on a quarterly basis and the results are shared with the IAS Technical Committees whose activities they support, and when appropriate, we take hard decisions to retire underperforming AEs.
In addition, we periodically calculate overall performance data for our Society leadership that also can be used to determine how individuals compare with the total AE population. By looking at the entire picture, we can identify anomalies and determine if they represent problems that need to be addressed, or are rather just outliers in the overall performance of the Society. For example, the frequency distribution of average first decision time for each AE shown here discloses a few outliers – several are known situations involving AEs associated with Technical Committees whose traditions inevitably result in a longer time to complete the first decision, and also a temporary situation involving an otherwise well-performing AE whose attention was distracted by a job change during the period of measurement.
The frequency distribution of AE workload also shows wide variation. Because this reflects only a narrow window of time, there are naturally individuals in the population who were either ramping up, or phasing out, and therefore had fewer assignments during the measurement period.
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