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<h2>Hiring strategy = incentivize open research and reduce barriers for URMs</h2> <h3><strong>Incentize open research</strong></h3> <ul> <li>To reduce "traditional" barriers to conducting open research, we have to incentive open research practices, particularly for early career researchers who want to engage in open research, but often feel <a href="http://bulliedintobadscience.org" rel="nofollow">#BulliedIntoBadScience</a>. I positively value open research in job adverts (see the <strong><em>yellow highlighting</em></strong> in the adverts)</li> </ul> <h3><strong>Reduce barriers for URMs (underrepresented minorities) in the sciences</strong></h3> <p>To attempt to counteract my implicit biases, I try to build into the infrastructure of the hiring/selection process ways that prevent me from relying on implicit biases to select team members 1) I make sure the language is <a href="http://gender-decoder.katmatfield.com/results/97f9ce9b-9489-469c-af91-037372f8f6e1" rel="nofollow">feminine-coded</a> which has been shown to encourage female applicants and not to deter male applicants 2) I avoid <a href="https://twitter.com/cricketcrocker/status/913472693059690496" rel="nofollow">buzzwords</a> and stated <a href="https://twitter.com/mikamckinnon/status/913474567032651776" rel="nofollow">needed</a> skills rather than trainable skills 3) I ensure that consideration of diversity is an active part of the recruitment process and not just an afterthought (see the <strong><em>purple highlighting</em></strong> in the adverts)</p> <h3><strong>Grackle project adverts that incorporate these goals</strong></h3> <ul> <li>2019-05 <a href="https://osf.io/7f6mr/" rel="nofollow">Postdoc</a> @ UCSB/MPI </li> <li>2017-11 <a href="https://osf.io/y5v76/" rel="nofollow">Research Technician</a> @ UCSB/MPI</li> </ul> <h2>After the advert, now what? Strategies for interviewing and selecting candidates, and creating a more inclusive environment</h2> <h4><strong>Interviewing</strong></h4> <ul> <li>Before starting an interview, read <a href="https://twitter.com/LoganCorina/status/910447340393287680" rel="nofollow">5 ways</a> to combat implicit biases</li> </ul> <h4><strong>Recruitment goal: undergraduates</strong></h4> <p>Our <strong>goal is to recruit a diverse team of undergrads</strong> (note: ASU undergrads in STEM=<a href="https://facts.asu.edu/Pages/Enrollments/STEM-Enrollment-Trends-by-Discipline.aspx" rel="nofollow">65% white, 36% female, 2016 data</a>. Compare with <a href="https://www.collegefactual.com/colleges/arizona-state-university/student-life/diversity/" rel="nofollow">university-wide stats</a>), which is consistent with ASU's <a href="https://asunow.asu.edu/content/stem-grows-so-do-efforts-help-students-succeed" rel="nofollow">goal</a>. Therefore, it is very important that we target Underrepresented Minorities (URM) in STEM when advertising research opportunities to ensure we have a diverse pool to choose from. </p> <p>We <strong>target our recruiting efforts to URM groups</strong> (e.g., the local <a href="https://www.sacnas.org" rel="nofollow">SACNAS</a> chapter) because we know that URMs haven't necessarily had access to or been trained to seek out research opportunities. Therefore, we invest more in reaching out to these groups and sharing what research experience can do for their career.</p> <p>We tend to receive a few applications at a time every month or so. Our strategy is to accept students who have submitted complete applications (unless there is something in their application that suggests they wouldn't be a good fit for the project) until the lab is full, and then put subsequent applicants on a waiting list and interview them when an opening arises.</p> <p>We interview applicants, but only accept those that keep our overall team percentage (over the course of our whole project) at <a href="https://twitter.com/LoganCorina/status/879606245891735552" rel="nofollow">at least 35% URMs</a>. So far, we have been able to accept everyone who has submitted a complete application.</p> <h4><strong>Making team members feel included</strong></h4> <ul> <li>See our <a href="http://corinalogan.com/ethics.html" rel="nofollow">Lab Code of Conduct</a> (here is another great one by <a href="http://theramirezgroup.org" rel="nofollow">Steve Ramirez</a>)</li> <li><a href="http://science.sciencemag.org/content/357/6356/1101" rel="nofollow">Puritty et al. 2017</a> wrote an excellent article and I <a href="https://twitter.com/LoganCorina/status/911161001202110464" rel="nofollow">tweeted</a> about it.</li> <li>Tips from <a href="https://www.murrayedwards.cam.ac.uk/about/Collaborating-with-Men" rel="nofollow">Collaborating with Men</a> project</li> <li>Give <a href="https://twitter.com/LoganCorina/status/879604731123027969" rel="nofollow">fun talks</a> because it makes people feel more included</li> <li>Open data might be good for science, but not always for URMs. <a href="https://twitter.com/LoganCorina/status/868487188450856960" rel="nofollow">Storify</a> on #OpenGlobalSouth</li> <li>Prestige = subjectively defined by the <a href="https://twitter.com/LoganCorina/status/868491581145444352" rel="nofollow">privileged</a> #OpenGlobalSouth</li> <li>Too few students from disadvantaged backgrounds make it into science: <a href="https://twitter.com/Protohedgehog/status/869312773540335617" rel="nofollow">Is science only for the rich?</a></li> <li>Discuss <a href="https://twitter.com/jayvanbavel/status/1003023518781632514" rel="nofollow">failures and setbacks</a> at lab meetings </li> </ul> <h4><strong>Writing unbiased letters of recommendation</strong></h4> <ul> <li>Do not use the <a href="https://twitter.com/WascherClaudia/status/987653021898301440" rel="nofollow">candidate's name</a>. Refer to them as "the candidate" or "the applicant"</li> <li>Use "they" rather than "she" or "he"</li> <li>Make sure the letter is <a href="http://gender-decoder.katmatfield.com" rel="nofollow">masculine-coded</a> because this is perceived as more impressive</li> </ul> <h2>Why this matters & what to do about it</h2> <p>The problem with using and promoting metrics in selection processes is that people with more privilege are much more likely to have access to opportunities that allow them to obtain higher scores on these metrics (e.g., How to be an Antiracist by Kendi <a href="https://www.ibramxkendi.com/how-to-be-an-antiracist" rel="nofollow">https://www.ibramxkendi.com/how-to-be-an-antiracist</a>). However, these metrics have nothing to do with the excellence or quality of the research. For example, most people who publish in the more well known journals are white (Maas et al. 2021 <a href="https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/conl.12797#.YD41lNXIrQZ" rel="nofollow">https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/conl.12797#.YD41lNXIrQZ</a>, Wu 2020 <a href="https://www.nytimes.com/2020/10/30/science/diversity-science-journals.html" rel="nofollow">https://www.nytimes.com/2020/10/30/science/diversity-science-journals.html</a>), which indicates that the journal's process for deciding to accept an article is likely racist. This is not surprising given that most editors are white men from the US or the UK (Palser et al. 2021 <a href="https://www.biorxiv.org/content/10.1101/2021.02.15.431321v1" rel="nofollow">https://www.biorxiv.org/content/10.1101/2021.02.15.431321v1</a>). Therefore, relying on publication metrics as an indicator of research excellence is racist and sexist.</p> <p>Apply antiracist action to selection processes from the application adverts to educating the evaluators. For example, evaluators of applications need explicit instructions to ignore metrics and address their implicit biases, and the infrastructure of the evaluation sheets should be changed such that it prevents reviewers from falling back on implicit biases.</p> <ul> <li> <p><strong>Women and Global South strikingly underrepresented among top‐publishing ecologists</strong>: "Many opportunities for increasing representation of women and scientists from the Global South are straightforward and therefore should be implemented immediately in scientific best practice" Maas et al 2021 <a href="https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/conl.12797#.YD41lNXIrQZ.twitter" rel="nofollow">https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/conl.12797#.YD41lNXIrQZ.twitter</a> . Tweet: <a href="https://twitter.com/biobiiana/status/1366734572315148296" rel="nofollow">https://twitter.com/biobiiana/status/1366734572315148296</a></p> </li> <li> <p><strong>"Editorial positions in the 50 most impactful neuroscience & psychology journals are not balanced in gender or geographical representation"</strong> Palser, Lazerwitz, Fotopoulou, 2021, <a href="https://www.biorxiv.org/content/10.1101/2021.02.15.431321v1" rel="nofollow">https://www.biorxiv.org/content/10.1101/2021.02.15.431321v1</a>. Tweet: <a href="https://twitter.com/Katlab_UCL/status/1362434530599198727" rel="nofollow">https://twitter.com/Katlab_UCL/status/1362434530599198727</a></p> </li> <li> <p>“Systemic racism refers to the well documented fact that most of our institutions—in politics, law, education, and health care, to name a few—are <strong>fundamentally organized according to assumptions and policies that work to the disadvantage of communities of color, and Blacks in particular</strong>.” Adia Harvey Wingfield, 2020 <a href="https://science.sciencemag.org/content/369/6502/351" rel="nofollow">https://science.sciencemag.org/content/369/6502/351</a></p> </li> <li><strong>Racism in science: we need to act now</strong> by Michael Eisen, Editor-in-Chief of eLife, 2020. “The reality is this IS a solvable problem: we have just chosen not to solve it.” “There is ample evidence that the entire system of science evaluation of which eLife is a part is structurally biased against Black scientists, and that significant changes are required to fix it.” “a system built around dispensing limited markers of prestige is fundamentally incompatible with true fairness” <a href="https://elifesciences.org/articles/59636" rel="nofollow">https://elifesciences.org/articles/59636</a> </li> <li><strong>Best practices: recruiting and retaining faculty and staff of color from Western Washington University</strong>. Which includes: Job announcements shaped to attract diversity (p.16) <a href="https://docplayer.net/3063483-Best-practices-recruiting-retaining-faculty-and-staff-of-color.html" rel="nofollow">https://docplayer.net/3063483-Best-practices-recruiting-retaining-faculty-and-staff-of-color.html</a> </li> <li><strong>Anti-racist hiring practices and our collective responsibility in this moment</strong> by Jessie Mawson, 2020 <a href="https://www.talentbeyondboundaries.org/blog/anti-racist-hiring-practices-and-our-collective-responsibility-in-this-moment" rel="nofollow">https://www.talentbeyondboundaries.org/blog/anti-racist-hiring-practices-and-our-collective-responsibility-in-this-moment</a> </li> <li><strong>Moving beyond business as usual: how to make your selection practices more equitable</strong> by Trisa Kern <a href="https://mielegalaid.org/system/files/dl/AntiRacistKern.pdf" rel="nofollow">https://mielegalaid.org/system/files/dl/AntiRacistKern.pdf</a> </li> <li><strong>Equity-centered design framework</strong>: how to change your infrastructure and prevent yourself from reverting to implicit/explicit biases against particular groups of people <a href="https://dschool.stanford.edu/resources/equity-centered-design-framework" rel="nofollow">https://dschool.stanford.edu/resources/equity-centered-design-framework</a> </li> <li>The <strong>Declaration on Research Assessment</strong> is working to change how researchers are evaluated by moving away from metrics and evaluating research quality instead <a href="https://sfdora.org" rel="nofollow">https://sfdora.org</a> </li> <li><strong>Project Implicit</strong>: to learn about what implicit biases you might have <a href="https://implicit.harvard.edu/implicit/education.html" rel="nofollow">https://implicit.harvard.edu/implicit/education.html</a> </li> </ul>
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