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Benchmarks How? Which? Who? Why?

Benchmarks How? Which? Who? Why?. Gender Equity Project Virginia 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

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Benchmarks How? Which? Who? Why?

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  1. Benchmarks How? Which? Who? Why? Gender Equity Project Virginia Valian & Vita Rabinowitz Hunter College 10 May 2004

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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)

  7. 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

  8. 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)

  9. 2 Administrative 18 Retired 1 3 Resigned 12 Promoted 5 4 Retired 1 Resigned 8 Promoted 34 New Hires 10 Resigned Faculty Flux* at Hunter College Total natural and social science faculty, 1998-2003 172 170 Full Associate Assistant Spring 2003 Spring 1998 *Thanks to WHOI for development of this flux chart.

  10. 1 Administrative 13 Retired 1 2 Resigned 8 Promoted 3 4 Retired 1 Resigned 5 Promoted 20 New Hires 3 Resigned Faculty Flux* at Hunter College Male natural and social science faculty, 1998-2003 113 113 Full Associate Assistant Spring 2003 Spring 1998 *Thanks to WHOI for development of this flux chart.

  11. 1 Administrative 5 Retired 1 Resigned 4 Promoted 2 3 Promoted 14 New Hires 7 Resigned Faculty Flux* at Hunter College Female natural and social science faculty, 1998-2003 59 57 Full Associate Assistant Spring 2003 Spring 1998 *Thanks to WHOI for development of this flux chart.

  12. Which Question: could a school do well on most of the benchmarks but not have equal professional development and satisfaction of ♀ and♂ ?

  13. 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

  14. 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 ♂

  15. Which • add recruitment! • Fall 2003 • social science: 5/9 • natural science: 4/8

  16. Which add 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

  17. 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

  18. 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

  19. Why? window on institutional effectiveness • discover gaps and inefficiencies in non-gender record-keeping, leading to better-functioning offices

  20. 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

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