lessons learned from programs for urm scientists

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Lessons learned from programs for URM scientists What is the problem? What do we need to know to develop and implement better programs? Anthony L. DePass PhD Associate Dean for Research Long Island University-Brooklyn

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Lessons learned from programs for URM scientists. What is the problem? What do we need to know to develop and implement better programs?. Anthony L. DePass PhD Associate Dean for Research Long Island University-Brooklyn. The Problem. - PowerPoint PPT Presentation

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Page 1: Lessons learned from programs for URM scientists

Lessons learned from programs for URM scientists

What is the problem? What do we need to know to develop and implement better programs?

Anthony L. DePass PhDAssociate Dean for Research Long Island University-Brooklyn

Page 2: Lessons learned from programs for URM scientists

The ProblemTenured/Tenure track faculty at top 50 departments (The Nelson Diversity

Surveys)White Black Hispanic Native Am.

Chemistry 1497 (91.2%)

18 (1.1%) 22 (1.3%) 3 (0.2%)

Physics 1715 (86.3%)

12 (0.6%) 38 (1.9%) 1 (0.05%)

Math 1764 (84.7%)

19 (0.9%) 55 (2.6) 3 (0.1%)

Comp Sci. 1032 (77.5%)

4 (0.3%) 17 (1.3%) 0

Psychology 1481 (90.2%)

44 (2.7%) 54 (3.3%) 5 (0.3%)

Biology 3232 (88.9%)

37 (1.0%) 69 (1.9%) 4 (0.1%)

Page 3: Lessons learned from programs for URM scientists

S&E doctorates awarded to U.S. citizens and permanent residents, by field and race/ethnicity: 1997–2004

Field and race/ethnicity 1997 1998 1999 2000 2001 2002 2003 2004

All S&E 18,393 18,257 17,567 17,114 16,346 15,512 15,715 15,721

White 13,828 14,004 13,719 13,443 12,760 11,913 12,024 12,018

Asian a 2,529 2,135 1,932 1,706 1,617 1,616 1,511 1,491

Black 615 644 715 710 703 685 664 746

Hispanic 658 754 722 729 674 724 741 715

American Indian/Alaska Native

79 96 114 88 73 70 73 61

Other/unknown race/ethnicity b 684 624 365 438 519 504 702 690

NSF- http://www.nsf.gov/statistics/wmpd/graddeg.htm

Page 4: Lessons learned from programs for URM scientists

Implications

• Diversity of the scientific workforce

• Underutilization of domestic potential for highly skilled/educated segment of the workforce

• Resource allocation

• Disparities in health and quality of life

Page 5: Lessons learned from programs for URM scientists

Proposed Solutions

• Increase representation at the highest levels (PhD)

• Fund interventions at various levels in the pipeline

Page 6: Lessons learned from programs for URM scientists

Approach• Intuitive but not investigative• Goal focused on predetermined outcome without much

credit given to “productive diversions”• Little consideration of broader context of factors involved

in career choices• Little research evidence that link activities to objectives• Non standard evaluation measures and techniques with

no organized means for dissemination • No systematic identification of best practices and training

of program directors• Lack of employment of scholarship in the development of

programs

Page 7: Lessons learned from programs for URM scientists

Considerations• Are goals and objectives appropriate and/or realistic?• Training model?• Definition of professional success• Factors outside of academic accomplishments that

determine “success”• Inherent “hostility” of the “successful working

environment” and its impact on retention• Pedigree system and its impact based on where

minorities are trained• Allocation of resources (based on predictors) that miss

the mark on broadening participant pool (grades vs access)

• The growing sex divide

Page 8: Lessons learned from programs for URM scientists

S&E doctorates awarded to U.S. citizens and permanent residents, by field and race/ethnicity: 1997–2004

Field and race/ethnicity 1997 1998 1999 2000 2001 2002 2003 2004

All S&E 18,393 18,257 17,567 17,114 16,346 15,512 15,715 15,721

White 13,828 14,004 13,719 13,443 12,760 11,913 12,024 12,018

Asian a 2,529 2,135 1,932 1,706 1,617 1,616 1,511 1,491

Black 615 644 715 710 703 685 664 746

Hispanic 658 754 722 729 674 724 741 715

American Indian/Alaska Native

79 96 114 88 73 70 73 61

Other/unknown race/ethnicity b 684 624 365 438 519 504 702 690

NSF- http://www.nsf.gov/statistics/wmpd/graddeg.htm

Page 9: Lessons learned from programs for URM scientists
Page 10: Lessons learned from programs for URM scientists

Racial/ethnic distribution of S&E bachelor's degrees awarded to U.S. citizens and permanent residents, by field: 1995–2004

(Percent)

Field and race/ethnicity 1995 1996 1997 1998 2000 2001 2002 2003 2004

White

All fields 78.5 77.4 76.5 75.6 73.7 72.9 72.2 71.4 70.7

S&E 75.9 74.8 73.5 72.5 70.5 69.7 69.2 68.5 67.8

Black

S&E 7.4 7.7 8.0 8.2 8.6 8.7 8.7 8.7 8.8

Hispanic

All fields 5.9 6.2 6.5 6.7 7.3 7.4 7.5 7.6 7.7

S&E 5.9 6.2 6.5 6.8 7.3 7.4 7.5 7.6 7.6

American Indian/Alaskan Native

All fields 0.6 0.6 0.6 0.7 0.7 0.7 0.7 0.7 0.7

S&E 0.5 0.6 0.6 0.6 0.7 0.7 0.7 0.7 0.7

NSF- http://www.nsf.gov/statistics/wmpd/graddeg.htm

Page 11: Lessons learned from programs for URM scientists

Paradigm Shift• Move towards hypothesis based investigative

approach – Funding mechanism– Incorporation of relevant expertise (economics and

the social, behavioral and computational sciences)– Developing and sustaining a relevant community of

scholars

• Greater interaction between programs at the administrative level

• Emphasis on measurable outcomes and institutional impact

Page 12: Lessons learned from programs for URM scientists

End