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		<h2><b>A response to the community on IA2 participant selections</b></h2>
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<p>Please see our <a href="https://outerspace.stsci.edu/download/attachments/40927621/IA2_Letter_to_community.pdf">letter in response</a> to some concerns communicated in the community with regards to the limited space and our participation selection process. 
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Inclusive Astronomy 2 Participant Selection Procedure

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To maximize equitability, the LOC explored two options:

A) Accept all persons who self-identified as being a member of any of the minority groups identified on the pre-registration form.

B) Calculate the percentage of pre-registrants who self-identified as being a member of any of the minority groups on the pre-registration form (Q2-Q7).  Accept, at a minimum, the same percentage of participants as pre-registrants in these groups.

We found that Option A would be impossible to implement given the number of pre-registrants who self-identified as being a member of any of the minority groups listed on the pre-registration form.  170 people identified as having a gender identity that is minoritized in astronomy (Q3), which is, alone, more than the number of people we could admit through the selection process. 155 people answered “yes” to any of Q2, Q4, Q5, and Q6 (i.e., not including gender minority).  Of these 155 people, 70% identify as being in an early career stage. Due to the limitations previously mentioned on financial support of early-career participants, admitting all of these people would not be possible. However, even if we had opted to use a flat registration fee, choosing these 155 people without considering Q1, Q3, or Q8 would also be arbitrarily exclusive.

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In this section, we describe every step we took from anonymized demographics to Entrofy-selected participants.

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1. Go through “other” demographic question (Q7) and re-categorize if appropriate

Q7 above allowed pre-registrants to add additional ways in which they identify as a minority in the field.  We found that five pre-registrants answered this question by self-identifying as one of the minority groups we had already identified, so we used those responses to update the answers to the relevant question(s).  There were several other things mentioned by participants, such as first generation American (or immigrant in their country of origin) or first generation college student. Since we did not ask all pre-registrants to address these categories, we did not feel that it would be fair or equitable to use these added categories in the selection criteria.  Future conference organizers may wish to include these, and other, additional categories.

2. Remove members of LOC/SOC and consulting members

Our LOC membership changed during the course of our planning, so some people that had pre-registered for the conference ended up later joining the LOC as members or consulting members.  We did not include LOC/SOC demographics in our selection criteria, primarily because they would be difficult to truly anonymize, so we didn’t want to require members to disclose this information.  Therefore, LOC/SOC members were removed from the selection list.  

3. Remove duplicates 

Some pre-registrants sent in multiple applications, either because they applied to give more than one presentation or they edited their response.  These duplicates were removed to make sure the demographic fractions were accurate and so that no person would have a higher probability of being selected.

4. Set targets for each demographic question

For a given category, when setting the target fractions (e.g., for “Yes” and “No” answers) in Entrofy, the fractions can be set in two ways:

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We recognize that an individual can have multiple marginalized identities within the groups that we identified.  We note that this is why the percentages from the 3rd or 6th columns in Table 1 (see end of document) add up to larger than 100%.  We do not explicitly take these multiply-minoritized identities into consideration when setting our targets in Entrofy. However, as shown in Table 3, the selection process results in a higher fraction of participants with multiple-minority identities than in the original applicant pool.

5. Run Entrofy

We run Entrofy through a Jupyter notebook.  You can find the notebook that follows the method that we used to select participants from a simulated sample that has similar (though not identical) demographics to our actual sample, on our website at: https://outerspace.stsci.edu/display/IA2/Participant+Selection

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Table 1: Categories that influenced selection.

*This cap was set to ensure early-career participants could be financially supported by supplementing their costs with fees from the mid- to late-career participants and from grants received.

Table 2: Other categories that did not influence selection.

Table 3: Representation and minoritized identities summary.

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notebooks notebooks

Example Entrofy Notebooks

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