Women in Astronomy IV Demographic Hack Session Lead by Dara Norman and Sarah Tuttle Saturday, June 10, 2017

Hack Session Structure This presentation (~20min) Brainstorm (~10-15min) Hack in small groups (~60 min) Report out (~20-30 min) Note taking equipment useful, Google doc, list of links

Outline Why demographics are important What to collect : The usual at meetings versus this Hack session What to collect : Who is in the workforce Plus Intersectionality What/where/how do they work? How/Who to survey: Surveys: The many vs fewer Reaching the target audience (not just AAS members) Demographics to inform policy (e.g., how do we make decisions about field advancement?) Presentation, presentation, presentation Tying scientific outcomes and advances to workforce and policy making demographics

Demographics are Important The usual at meetings Setting the stage Assessing ‘where we are’ This Hack session: What are the outcomes we want How can demographics inform the path to those outcomes

Intersectionality Background Kimberlè Crenshaw & Degraffenreid vs General Motors lawsuit, 1977 Structural & Political Intersectionality Appropriation of the term here to include not just personal information, but workforce information.

Intersectionality: Race/Gender Research funding (e.g., grants) is currently not tied to metrics or progress on the inclusion of underrepresented and disenfranchised groups. “Broadening Participation” must be about workforce and research participation, not just public outreach and education. Demographic anecdote: I was recently at a science meeting for a large astronomy project and while this project has and extensive education/outreach effort planned, I was the only African American scientist of 250 participants over 3 days. Inclusion will not occur to that group unless it is brought to their attention in a significant way. The most significant way is through an impact on their funding.

Intersectionality: Gender/Scientific Area To mitigate bias, increase numbers of women and minorities in job applicant pools through active and open recruiting. Need to know when your job application pool adequately represents the available community. Demographic anecdote: Hiring for a senior staff position that requires a data science background along with knowledge of Astronomy. Is having 2 women of 16 applicants in this job pool search reasonable? What is the available pool?

Structural Intersectionality Science leadership and policy making activities (e.g., committee membership and input to committees) often come from too narrow a group of scientists. Narrow groups often underestimate barriers to inclusion that stymie good ideas. Demographic anecdote: A recent NRC committee for future development of astronomy resources had no committee members from small teaching universities. The main way they chose to get input from the community was through submitted white papers, but the only timescale for submission of these intersected the start of the school year (early Oct) when faculty with significant teaching are unavailable. This creates a significant bias in who can participate in the discussion. No one on the committee thought to bring that to anyone's attention. Perhaps advisory committees should be encouraged to look at ‘input’ demographics/metrics BEFORE final reports are finalized. Agencies/ bodies receiving these reports should request these input demographics.

Presentation of Information Conclusions and findings do not provide opportunities for agency action on issues of concern. Recommendations from advisory committees are needed. Pertinent demographic information on the workforce must be shown to be tied to scientific outcomes. Demographic anecdote: The 2010 Decadal Survey contained only one recommendation in the demography section related to making student aware of career opportunities beyond research astronomy that exploit their astronomy degree. Acknowledgement that little progress has been made on improving URM participation and inclusion of women at senior level were chapter ‘conclusions’ thus no direct initiatives have been implemented or taken. Perhaps advisory committees should be encouraged to look at ‘input’ demographics/metrics BEFORE final reports are finalized. Agencies/ bodies receiving these reports should request these input demographics.

This Hack Session: The Goal Report findings, conclusions and recommendations that will lead to a white paper(s) submitted to the decadal survey panels on the need for the collection and reporting of demographic data that can be used to inform structural changes in astronomy and astrophysics to better support our science and the scientific workforce. Resources in Google Doc : https://drive.google.com/drive/folders/0B3gWwXXPvxNVOWY 4RnBVaU1CUXc?usp=sharing

This Hack Session: Some Questions What are the questions/issues/concerns we want to address Why and how do we want to address them?What are the reasons we want demographic information in Astronomy? How do we address  ‘intersectional’ information along a number of vectors, race, gender, etc., as well as research field, funding status, etc. to inform us about the structure of the astronomical workforce and how decisions about scientific resources are made. What information is already available?  What still needs to be collected? Are there better ways to collect needed data? How do we present/use this data in professional situations to make practical differences?

This Hack Session: Structure Group brainstorm on additional topics beyond the 4 suggested here Split into groups of 4-6 (or so) to make suggestions about answering the questions posed for each questions/issues/concerns we want to address. (e.g., what is available/needed; how/ where to present data; role of intersectionality in addressing the issue) Report out from small groups to the larger group on suggestions and findings. IF time – begin to craft scope of white paper(s) to be continued on Sunday morning.

Suggested Policy Concerns 1 Research funding (e.g., grants) is currently not tied to metrics or progress on the inclusion of underrepresented and disenfranchised groups. (EPO vs research participation) To mitigate bias, increase numbers of women and minorities in job applicant pools through active and open recruiting. (When is there adequate representation?) Science leadership and policy making activities (e.g., committee membership and input to committees) often come from too narrow a group of scientists. (Assessing barriers) Conclusions and findings do not provide opportunities for agency action on issues of concern. Recommendations from advisory committees are needed. (Findings into change) Graduate program, International, Undergraduate demographics URM+ leaving departments from where 2 3 4 6 7

Sunday, June 11 2017 White paper writing sessons White Paper Drafts Sunday, June 11 2017 White paper writing sessons

White Paper Draft considerations Keep the topic of WP simple and clear! Pick ONE outcome you would like to see to work on first. What is the background information that is needed to understand the problem? Do we have this background info currently or do we need to collect? Be specific and demonstrate where problems with collection are. What are you ASKING for? BE specific about what you want to see happen in order to make change. Give examples/models of how implementation of the change would work practically. Who must have ownership of making these changes? What are the resources needed? (money and time/people)

Remember the questions to answer in WP What are the questions/issues/concerns we want to address Why and how do we want to address them?What are the reasons we want demographic information in Astronomy? How do we address  ‘intersectional’ information along a number of vectors, race, gender, etc., as well as research field, funding status, etc. to inform us about the structure of the astronomical workforce and how decisions about scientific resources are made. What information is already available?  What still needs to be collected? Are there better ways to collect needed data? How do we present/use this data in professional situations to make practical differences?

Additional slides Resources ETC

Resource Documents

Resource links NSF includes the National Center for Science and Engineering Statistics. https://www.nsf.gov statistics/ , “The NCSES is the nation’s leading provider of statistical data on the U.S. science and engineering enterprise.” They regularly publish large statistical compendia such as “Science and Engineering Indicators” and “Women, Minorities, and Persons with Disabilities in Science and Engineering.” NSF demographic data tables: https://www.nsf.gov/statistics/2017/nsf17310/data.cfm American Institute of Physics: https://www.aip.org/statistics AIP’s Astronomy: https://www.aip.org/statistics/astronomy SESTAT: https://www.nsf.gov/statistics/sestat/ Scientists and Engineers Statistical Data System. This integrated data system is a unique source of longitudinal information on the education and employment of the college-educated U.S. science and engineering workforce. These data are collected through biennial surveys: The National Survey of College Graduates (NSCG) The National Survey of Recent College Graduates (NSRCG) (discontinued after 2010) The Survey of Doctorate Recipients (SDR) APS LGBT Study: https://www.aps.org/programs/lgbt/ 2010 Decadal Survey New Worlds, New Horizons https://www.nap.edu/read/12951/chapter/1 Astro Demography p117 in Astronomy in Society: https://www.nap.edu/read/12951/chapter/6 Symposium on the Science of Broadening Participation: http://sobp-conference.weebly.com/symposium-report.html