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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 PhD Associate Dean for Research Long Island University-Brooklyn. The Problem.

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Lessons learned from programs for URM scientists

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  1. 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

  2. The Problem Tenured/Tenure track faculty at top 50 departments (The Nelson Diversity Surveys)

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

  4. 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

  5. Proposed Solutions • Increase representation at the highest levels (PhD) • Fund interventions at various levels in the pipeline

  6. 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

  7. 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

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

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

  10. 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

  11. End

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