Benchmarks How? Which? Who?
Why?
Gender Equity ProjectVirginia Valian & Vita Rabinowitz
Hunter College
10 May 2004
Mandate: Institutionalization
Institutionalize collection of benchmarks at schools with NSF ADVANCE IT awards
ADVANCE teams may determine how it is to be done
ADVANCE teams may work with the institutional office that will take on the work
but ADVANCE must pass on the baton
Goal: Institutionalization
Institutionalize collection of benchmarks at all schools nation-wide
Requirements
• how-to manual, with solutions to problems of collecting, analyzing, and reporting benchmark data
• motivation
How to institutionalize
Problem: antiquated, inadequate, and decentralized data bases
• e.g., at Hunter, computerized data base only extends back to 1989; earlier material must be entered by hand
• e.g., at some institutions, different colleges or schools have their own data; difficult to integrate cross-school
How to institutionalize
Problem: no clear locus for collection and distribution of data
• IR? not all schools have an office for institutional research
• HR? not all human resource offices are accustomed to providing finished tables (as opposed to giving data to another office)
• diversity compliance? such offices vary widely in the scope of data they collect and report
How to institutionalize
Problem: data originate in different locations• some data are in HR: salary, date of hire,
date of reappointment, date of severance• some data (e.g., space allocation) are
scattered over several offices• some data (e.g., offer letters) are in chairs'
files, others in deans' files, others in provosts' files, others in no one's files (because not in writing)
How to institutionalize
Problem: some data are incommensurate across institutions
• distinguished chairs (e.g., at some institutions, named chairs are less prestigious than university chairs)
• department chairs (e.g., at schools with few resources, department chairs have few opportunities for leadership; are managers rather than leaders)
• chairs vs heads
How to institutionalize
Problem: hard to simultaneously present data fully and transparently
• need to work out data presentation
• faculty flux charts (initially conceptualized at Lamont-Doherty Earth Observatory; graphically developed by Woods Hole Oceanographic Institution)
Total natural and social science faculty, 1998-2003
170 172
Spring 1998 Spring 2003
8 Promoted
12 Promoted
3 Resigned
1 Resigned
10 Resigned
4 Retired
2 Administrative
18 Retired Full
Associate
Assistant
*Thanks to WHOI for development of this flux chart.
5
1
34 New Hires
Faculty Flux* at Hunter College
Male natural and social science faculty, 1998-2003
113 113
Faculty Flux* at Hunter College
5 Promoted
8 Promoted
2 Resigned
1 Resigned
3 Resigned
4 Retired
1 Administrative
13 Retired Full
Associate
Assistant
*Thanks to WHOI for development of this flux chart.
3
1
20 New Hires
Spring 1998 Spring 2003
Faculty Flux* at Hunter College
5759
Full
Associate
Assistant7 Resigned
1 Resigned
1 Administrative
5 Retired
3 Promoted
4 Promoted
Female natural and social science faculty, 1998-2003
2
14 New Hires
*Thanks to WHOI for development of this flux chart.
Spring 1998 Spring 2003
Which
Question: could a school do well on most of the benchmarks but not have equal professional development and satisfaction of ♀ and ♂ ?
Which – Hunter College
Spring 2003
♀ salaries equivalent to ♂♀ ~ 29% of nat sci Full Prof
♀ ~ 32% of soc sci Full Prof
♀ = 75% of Dist Profs (n=4)
♀ represented on decision-making committees at or above representation on faculty
Which – Hunter College
But:
♀ spend more time in rank in soc sci
♀ leave at Asst Prof more often than ♂(national trend)
♀ may be less productive than ♂♀ may have less informal power and
influence than ♂
Which
• add recruitment!– Fall 2003
• social science: 5/9• natural science: 4/8
Whichadd smaller-scale studies
• % ♀ colloquium speakers
• % ♀ and ♂ hired as function of prestige of PhD-granting institution (Nelson; Kuch)
• % ♀ and ♂ nominated for professional prizes, awards, and fellow status
• institutional rewards to faculty who work for gender equity and diversity
correlate smaller-scale study data with NSF-12
Why?workforce infrastructure
• demographics of population is changing much more rapidly than demographics of science
• if scientists are going to be evenly distributed across demographic categories, need to monitor progress toward that end
Why?external funding and influence
• demonstrate to funders that good record-keeping procedures are already in place
• increase competitiveness for grants targeting women and minorities
• demonstrate to state and national legislators that support is necessary to continue serving needs of constituents
Why?
window on institutional effectiveness
• discover gaps and inefficiencies in non-gender record-keeping, leading to better-functioning offices
Why?
continuous thread
• students need additional ways of judging which schools will do well by them: equity benchmark reporting is one way
• faculty need additional ways of learning where they are likely to flourish: equity benchmark reporting is one way