NOTE: The American Indian and Alaska Native Head Start Family and Child Experiences Survey (AI/AN FACES) data and User Guide will be released in fall 2017. The Head Start Family and Child Experiences Survey (FACES) is a major source of information on Head Start programs and the children and families they serve. Since 1997, FACES has conducted studies in a nationally representative sample of Head Start programs, but has historically not included Region XI (programs operated by federally-recognized tribes), whose programs are designed to serve predominantly American Indian and Alaska Native (AI/AN) children and families. The American Indian and Alaska Native Head Start Family and Child Experiences Survey (AI/AN FACES), the first national study of Region XI AI/AN Head Start children and families, is designed to fill this information gap. The design of AI/AN FACES has been informed by members of the AI/AN FACES Workgroup which includes tribal Head Start directors, researchers with expertise working with tribal communities, Mathematica Policy Research study staff, and federal officials from the Office of Head Start, Region XI, and the Office of Planning, Research and Evaluation. Building on FACES as the foundation, members of the AI/AN FACES Workgroup have shared insights and information on the kinds of information needed about children and families served by Region XI AI/AN Head Start programs (including children's development and school readiness, parent and family demographics, health, and program engagement, and teacher, classroom, and program characteristics). Members also provided input on recruitment practices and study methods that are responsive to the unique cultural and self-governing contexts of tribal Head Start programs. Data collection with Region XI children, families, classrooms, and programs took place in the Fall of 2015 and the Spring of 2016. Twenty-one Region XI Head Start programs participated. Procedures for tribal review and approval in each of those 21 communities were followed. Information about this study has been shared broadly with tribal Head Start programs and tribal leaders via OHS tribal consultations, nationally-broadcast webinars, National Indian Head Start Directors' Association Board of Directors (NIHSDA) annual conferences, the 2016 ACF National Research Conference on Early Childhood, and the Secretary's Tribal Advisory Council (STAC) December 2014 and 2016 meetings.

According to a 2020 survey, 40 percent of Indian American respondents in the United States had obtained a postgraduate degree. Only one percent of survey participants did not have any high school education.

Institutions of higher education (IHE) throughout the United States have a long history of acting out various levels of commitment to diversity advancement, equity, and inclusion (DEI). Despite decades of DEI “efforts,” the academy is fraught with legacies of racism that uphold white supremacy and prevent marginalized populations from full participation. Furthermore, politicians have not only weaponized education but passed legislation to actively ban DEI programs and censor general education curricula (https://tinyurl.com/antiDEI). Ironically, systems of oppression are particularly apparent in the fields of Ecology, Evolution, and Conservation Biology (EECB)–which recognize biological diversity as essential for ecological integrity and resilience. Yet, amongst EECB faculty, people who do not identify as cis-heterosexual, non-disabled, affluent white males are poorly represented. Furthermore, IHE lack metrics to quantify DEI as a priority. Here we show that only 30.3% of US-faculty positions advertised in EECB from Jan 2019-May 2020 required a diversity statement; diversity statement requirements did not correspond with state-level diversity metrics. Though many announcements “encourage women and minorities to apply,” empirical evidence demonstrates that hiring committees at most institutions did not prioritize an applicant’s DEI advancement potential. We suggest a model for change and call on administrators and faculty to implement SMART (i.e., Specific, Measurable, Achievable, Realistic, and Timely) strategies for DEI advancement across IHE throughout the United States. We anticipate our quantification of diversity statement requirements relative to other application materials will motivate institutional change in both policy and practice when evaluating a candidate’s potential “fit”. IHE must embrace a leadership role to not only shift the academic culture to one that upholds DEI, but to educate and include people who represent the full diversity of our society. In the current context of political censure of education including book banning and backlash aimed at Critical Race Theory, which further reinforce systemic white supremacy, academic integrity and justice are more critical than ever. Methods Here we investigated the (lack of) process in faculty searches at IHE for evaluating candidates’ ability to advance DEI objectives. We quantified the prevalence of required diversity statements relative to research and/or teaching statements for all faculty positions posted to the Eco-Evo Jobs Board (http://ecoevojobs.net) from January 2019 - May 2020 as a proxy for institutional DEI prioritization (Supplement). We also mapped the job posts that required diversity statements geographically to gauge whether and where diversity is valued in higher education across the US. Data analysis We pulled all faculty jobs posted on Eco-Evo jobs board (http://ecoevojobs.net) from Jan 1, 2019, to May 31, 2020. For each position, we recorded the Location (i.e., state), Subject Area, Closing Date, Rank, whether or not the position is Tenure Track, and individual application materials (i.e., Research statement, Teaching statement, combined Teaching and Research statement, Diversity statement, Mentorship statement). Of the 543 faculty positions posted during this time, we eliminated 299 posts because the web links were broken or application information was no longer available (i.e., “NA”), leaving 244 faculty job posts. For each of the retained posts, we coded the requirement of teaching, research, diversity, and/or mentorship statements as follows:

"Yes” = statement required “No” = statement not required “Other” = application materials did not explicitly require a Diversity Statement (i.e., option or suggested that applicants include a statement on diversity and inclusion as a component of their teaching and/or research statement or in their cover letter)

Data visualization We created a Sankey diagram using Sankey Flow Show (THORTEC Software GmbH: www.sankeyflowshow.com) to compare diversity and representation from the general population, through (Science, Technology, Engineering, and Mathematics) STEM academia (a career hierarchy often referred to as the “leaky pipeline”). We procured population data from the US Census Bureau (US Department of Commerce: https://www.census.gov/quickfacts/fact/table/US/PST045219) and quantified the diversity/representation in Conservation Biology (https://datausa.io/profile/cip/ecology-evolution-systematics-population-biology#demographics) and Ecology (https://datausa.io/profile/cip/conservation-biology) using Data USA (developed by Deloitte Touche Tohmatsu Limited and Datawheel). We used the 2015 Diversity Index (produced by PolicyLink and the USC Program for Environmental and Regional Equity: https://nationalequityatlas.org/indicators/Diversity_index/Ranking:33271/United_States/false/Year(s):2015/) to quantify relative ethnic diversity per state, and graphed Figure 2B using the tidyverse, rgdal, broom, and rgeos packages in R (see Base code used to produce Figure 2 in R, below). The Diversity index measures the representation of White, Black, Latino, Asian/Pacific Islander, Native American, and Mixed/other race in a given population. A maximum possible diversity score (1.79) would indicate even representation of all ethnic/racial groups. We checked all figures using the Color Blindness Simulator (ColBlindor: https://www.color-blindness.com/coblis-color-blindness-simulator/) to maintain inclusivity.

This project is integrating scientific research in the Arctic with education and outreach, with a strong central focus on engaging undergraduate students and visiting faculty from groups that have had little involvement in Arctic science to date. Science and society in the United States will be stronger in the long-term if the scientific workforce more closely reflects the racial, ethnic, and cultural diversity of its residents. The Arctic research community currently does not. Of the Principal Investigators funded by NSF's Arctic programs in the past five years, only 1% were African American, Hispanic, Native American, or Alaska Native. This project is catalyzing change in these demographics by engaging faculty from Minority Serving Institutions (MSIs) and a diverse group of undergraduate students in cutting-edge Arctic research and providing them encouragement, mentoring, and opportunities to continue pursuing Arctic studies in subsequent years.

The central element of the project is a month-long research expedition to the Yukon River Delta in Alaska. The expedition provides a deep intellectual and cultural immersion in the context of an authentic research experience that is paramount for "hooking" students and keeping them moving along the pipeline to careers as Arctic scientists. The overarching scientific issue that drives the research is the vulnerability and fate of ancient carbon stored in Arctic permafrost (permanently frozen ground). Widespread permafrost thaw is expected to occur this century, but large uncertainties remain in estimating the timing, magnitude, and form of carbon that will be released when thawed. Project participants are working in collaborative research groups to make fundamental scientific discoveries related to the vulnerability of permafrost carbon in the Yukon River Delta and the potential implications of permafrost thaw in this region for the global climate system.

The Head Start Family and Child Experiences Survey (FACES) is a major source of information on Head Start programs and the children and families they serve. Since 1997, FACES has conducted studies in a nationally representative sample of Head Start programs, but has historically not included Region XI (programs operated by federally-recognized tribes), whose programs are designed to serve predominantly American Indian and Alaska Native (AI/AN) children and families. The American Indian and Alaska Native Head Start Family and Child Experiences Survey 2015 (AI/AN FACES 2015), the first national study of Region XI AI/AN Head Start children and families, is designed to fill this information gap. The design of AI/AN FACES 2015 has been informed by members of the AI/AN FACES 2015 Workgroup which includes tribal Head Start directors, researchers with expertise working with tribal communities, Mathematica Policy Research study staff, and federal officials from the Office of Head Start, Region XI, and the Office of Planning, Research and Evaluation. Building on FACES as the foundation, members of the AI/AN FACES 2015 Workgroup have shared insights and information on the kinds of information needed about children and families served by Region XI AI/AN Head Start programs (including children's development and school readiness, parent and family demographics, health, and program engagement, and teacher, classroom, and program characteristics). Members also provided input on recruitment practices and study methods that are responsive to the unique cultural and self-governing contexts of tribal Head Start programs. Data collection with Region XI children, families, classrooms, and programs took place in the Fall of 2015 and the Spring of 2016. Twenty-one Region XI Head Start programs participated. Procedures for tribal review and approval in each of those 21 communities were followed. Information about this study has been shared broadly with tribal Head Start programs and tribal leaders via OHS tribal consultations, nationally-broadcast webinars, National Indian Head Start Directors' Association Board of Directors (NIHSDA) annual conferences, the 2016 ACF National Research Conference on Early Childhood, and the Secretary's Tribal Advisory Council (STAC) December 2014 and 2016 meetings.

2018 DC School Report Card. STAR Framework student group scores by school and school framework. The STAR Framework measures performance for 10 different student groups with a minimum n size of 10 or more students at the school. The student groups are All Students, Students with Disabilities, Student who are At Risk, English Learners, and students who identify as the following ESSA-defined racial/ethnic groups: American Indian or Alaskan Native, Asian, Black or African American, Hispanic/Latino of any race, Native Hawaiian or Other Pacific Islander, White, and Two or more races. The Alternative School Framework includes an eleventh student group, At-Risk Students with Disabilities.Some students are included in the school- and LEA-level aggregations that will display on the DC School Report Card but are not included in calculations for the STAR Framework. These students are included in the “All Report Card Students” student group to distinguish from the “All Students” group used for the STAR Framework.Supplemental:Metric scores are not reported for n-sizes less than 10; metrics that have an n-size less than 10 are not included in calculation of STAR scores and ratings.At the state level, teacher data is reported on the DC School Report Card for all schools, high-poverty schools, and low-poverty schools. The definition for high-poverty and low-poverty schools is included in DC's ESSA State Plan. At the school level, teacher data is reported for the entire school, and at the LEA-level, teacher data is reported for all schools only.On the STAR Framework, 203 schools received STAR scores and ratings based on data from the 2017-18 school year. Of those 203 schools, 2 schools closed after the completion of the 2017-18 school year (Excel Academy PCS and Washington Mathematics Science Technology PCHS). Because those two schools closed, they do not receive a School Report Card and report card metrics were not calculated for those schools.Schools with non-traditional grade configurations may be assigned multiple school frameworks as part of the STAR Framework. For example, a K-8 school would be assigned the Elementary School Framework and the Middle School Framework. Because a school may have multiple school frameworks, the total number of school framework scores across the city will be greater than the total number of schools that received a STAR score and rating.Detailed information about the metrics and calculations for the DC School Report Card and STAR Framework can be found in the 2018 DC School Report Card and STAR Framework Technical Guide (https://osse.dc.gov/publication/2018-dc-school-report-card-and-star-framework-technical-guide).