class: center, middle, inverse, title-slide .title[ # Parent’s Choice or School’s Choice? Discrimination Against Students in Admission to Private, Charter, and Traditional Public Schools ] .author[ ### <p>Hussain Hadah, Patrick Button, Douglas Harris, Barbara Lundebjerg, Baris Alan <br></p> ] .date[ ### April 15 2026 ] --- layout: true <div style="position: absolute;left:20px;bottom:5px;color:black;font-size: 12px;">Hussain Hadah (Tulane/Murphy Institute) | Parent’s Choice or School’s Choice? | Lunch Seminar April 15 2026</div> <!--- | 15 April 2026--> --- <style type="text/css"> /* Table width = 100% max-width */ .remark-slide table{ width: auto !important; /* Adjusts table width */ } /* Change the background color to white for shaded rows (even rows) */ .remark-slide thead, .remark-slide tr:nth-child(2n) { background-color: white; } .remark-slide thead, .remark-slide tr:nth-child(n) { background-color: white; } </style> ## School Choice Programs are Expanding Rapidly - #### Education is strongly linked to economic mobility and non-economic benefits .tiny[.gray[**(Chetty et al., 2014, 2016)**]] - #### Minoritized groups, especially Black, Hispanic, and immigrant families, face educational disparities .tiny[.gray[**(e.g., Bergman & McFarlin, 2020; Hadah, 2025)**]] - #### While public and charter schools are available to all, there are still inequalities through: - .font70[Resource and teacher quality imbalances .tiny[.gray[**(Ferguson, 1991, Johnson, 2019; Sass et al., 2012)**]]] - .font70[Larger class sizes and course placement .tiny[.gray[**(Boozer & Rouse, 2001; Francis, De Oliveira, & Dimmitt, 2019)**]]] -- - #### Then there are private schools - .font70[Less affirming of minoritized groups and less accessible] - .font70[They can legally discriminate on any basis except race .tiny[.gray[**(Petrilli, 2017)**]]] --- ## American education is undergoing one of its most significant shifts in the last half-century - #### Milton Friedman (1955) popularized vouchers in the wake of Brown v. Board of Education - .font60[He tried to sell it knowing that southern states would use it to continue segregation] - .font60[Recent evidence affirms this interpretation .tiny[.gray[**(DeAngelis et al., 2019)**]]] - #### 8 states have universal vouchers .gray[.tiny[**(EdChoice, 2025)**]] - #### Voucher expansion aligns with broader discriminatory policy trends (e.g., anti-DEI, anti-CRT, etc.) - #### Some argue that this would expand educational opportunities for low-income families, the more rigorous and relevant research calls this into question -- - #### .brand-crawfest[To what extent do these programs discriminate against students is an open question] --- ## We will conduct an audit experiment of .brand-crawfest[public], .brand-crawfest[charter], and .brand-crawfest[private] schools in the US - We will send emails to receive admission information - We will randomize several characteristics of the students to test for discrimination - .brand-crawfest[**Race and Ethnicity]:** Black, Hispanic, White, Arab - .brand-crawfest[**LGBTQ+ Status]:** gay/lesbian vs. presumed straight and transgender vs. non-binary vs. presumed cis - .brand-crawfest[**Disability Status]:** ADHD, autism, no disability disclosed - **Academic achievement:** High vs low - **Socioeconomic Status (SES)/Income:** Ph.D. vs. MD vs. no mention - **Nativity:** US-born ("moving closer to my parents") --- ## We contribute to the literature in several ways - ##### We will be the first audit study to test for discrimination in access to education in .brand-crawfest[public], .brand-crawfest[charter], and .brand-crawfest[private] schools - .font70[No previous audit studies included private schools] - ##### First to test for discrimination against .brand-crawfest[LGBTQ+] and .brand-crawfest[Arab] people in access to education - ##### We will also test how some policies will influence discrimination - .font70[DEI/CRT bans and LGBTQIA+ policies] - ##### Determining where discrimination occurs and informing policy to counteract it - .font70[Testing mechanisms (e.g., statistical discrimination, implicit bias) ] - .font70[Spatial/school-level characteristics , such as district characteristics, segregation, and social views] --- class: segue-yellow background-image: url("assets/TulaneLogo.svg") background-size: 20% background-position: 95% 95% count:false # Data --- name: data-sec ## We purchased point of contact, from MDR Education dataset ### Sample includes verified K–12 contact data, prioritizing school secretaries, supplemented with principals, APs, deans, and counselors ### We have the contacts of 64,482 secretaries, 15,264 principals, 12,424 counselors, 895 APs, and 204 deans ### We exclude alternative/adult/detention/juvenile, single-sex, and specialized disability schools - **Final sample: 93,269 schools** -- **School and district charachteristics** using National Longitudinal School Database (NLSD) .tiny[.gray[(Carroll et al., 2023b)]] **State policy data (to be collected):** anti-DEI laws, vouchers, "Don't Say Gay" laws, etc. --- class: segue-yellow background-image: url("assets/TulaneLogo.svg") background-size: 20% background-position: 95% 95% count:false # Study Design --- name: design ## We will consider many dimensions .pull-left[ - #### At least 7 types of schools - .font70[**Private**: Catholic, Protestant, secular, and single-sex] - .font70[**Charter**: No-excuses/other, district/other authorizer] - .font70[**Traditional public schools**] ] .pull-right[ - #### 7 dimensions of potential discrimination - .font70[**Race and ethnicity** (Black, Hispanic, White, Arab) signaled through names] - .font70[**LGBTQ+ status** (lesbian, gay, trans girls and boys, non-binary)] - .font70[**Disability status** (ADHD, autism, no disability disclosed)] - .font70[**Academic achievement** (high vs. low)] - .font70[**Socioeconomic status** (Ph.D., MD, no mention)] - .font70[**Nativity** native-born vs. no mention] ] --- name: treat-arms-assign ## Assigning treatment arms - ### Schools without any 9th–12th grades → **automatically assigned to disability arm** - Signaling SOGI is unusual for younger students - ### Schools with any 9th–12th grade → **80% SOGI / 20% disability** - SOGI arm: child referenced as entering 9th grade or later - Disability arm: child referenced as entering any grade - #### Final assignment - **73,624** schools → disability arm; **19,645** schools → SOGI arm - 69,820 public, 7,054 charter, 16,395 private --- name: race-ethnicity-names ## We will use names to signal race and ethnicity - ### The names have been tested by Gaddis (2022; White, African American, and Hispanic names) and Baert, Lippens & Van Borm (2022; Arab) - ### We will assign a different race and ethnicity to each family in our email pairs: - Emails assigned to the disability treatment: probabilities 33% White, 23% Black, 23% Hispanic, and 21% Arab - Emails assigned to the SOGI treatment: probabilities 40% White, 30% Black, and 30% Hispanic --- name: sogi-treatment ## Signaling sexual orientation or gender identity - ### We will only use high school for this treatment arm - ### When we do signal SOGI, the mother’s email mentions that the child is either gay (20%), lesbian (20%), transgender (15% trans girl, 15% trans boy), or non-binary (10%) by adding - "[He/She/They] [is/are] [gay/lesbian/trans], and we are hoping to find a school that is [supportive / LGBT friendly]" - Mirroring language used in Pfaff et al. (2021) of religious beliefs --- name: disability-treatment ## Signaling disability status - ### For schools assigned to the disability treatment arm we will randomly assign the child to have: - Equal probabilities of ADHD or autism - The remaining emails will not mention a disability - ### We will add a sentence: - "[She/he] has an IEP for [her/his] ADHD" - "[She/he] is on the spectrum and will need to be taught in a separate classroom" --- name: academic-achievement ## Signaling academic achievement, socioeconomic status (SES), and nativity - ### We will signal academic achievement by mentioning that the child: - "typically gets As and Bs" - "typically gets Cs" - ### We will signal SES by either including or omitting degree information like "MD" or "PhD" in the mother’s email signature - ### Since name signals for Hispanics and Arabs could also signal "immigrant status", we will randomize phrasings that could signal nativity --- name: email-template ## Audit Study Email Template **From:** [MOTHER'S FIRST AND LAST NAME] (\<email address\>) **Subject:** [EMAIL SUBJECT] **Email Body:** [GREETING], [RECENTLY MOVED, RESEARCHING SCHOOLS] for our {daughter/son/child}, [CHILD's FIRST NAME]. {She/He/They} [IS IN] [GRADE] and [HAS ACADEMIC PERFORMANCE (Excluded for disability treatment arm)]. | **If assigned a disability:** | **If assigned to be LGBT:** | **Otherwise:** | |:-----|:-----|:-----| | [{She/He} is on the spectrum and will need to be taught in a separate classroom.] (50%) **OR** [{She/He} has an IEP for {her/his} ADHD.] (50%) | [She is trans] (25%) **OR** [He is trans] (17%) **OR** [They are non-binary] (18%) **OR** [She is lesbian] (20%) **OR** [He is gay] (20%) and we are hoping to find a school that is LGBT friendly. | No additional sentence. | [APPLICATION QUESTIONS] [VALEDICTION], [MOTHER'S FIRST AND LAST NAME] (50%) **OR** Dr. [" "], MD (25%) **OR** Dr. [" "], PhD (25%) --- ## Actual emails .pull-left[ <img src="hadah-ed-audit-presentation_files/figure-html/example1-1.png" alt="" width="120%" style="display: block; margin: auto 0 auto auto;" /> ] .pull-right[ <img src="hadah-ed-audit-presentation_files/figure-html/example2-1.png" alt="" width="120%" style="display: block; margin: auto 0 auto auto;" /> ] --- name: coding-response ## Coding response data - ### Primary outcome: positive response - It will be coded as 1 if the school responds to our email in a way that is helpful (e.g., answers a question) or encouraging within two weeks and 0 otherwise - ### Secondary outcome: Features of (un)helpful and discriminatory responses through qualitative thematic coding and large language models (LLMs) .font50[.gray[**(e.g., Skeen and Button, 2024)**]] - .font70[Analysis will correct for post-treatment bias .tiny[.gray[**(Coppock, 2019)**]]] - ### Going beyond most audit studies which usually only consider response rates --- name: communication-schools ## Communication with the Schools - There is an extensive literature on how to write the emails to the schools - We will send two emails to school administrators (available in the MDR Education data) - We will randomize the characteristics of the students in the emails to signal our dimensions of interest - The emails will be realistic and will ask for information about the admissions process - We used some of Doug's extensive contacts with educators to ensure the emails are realistic --- name: emailing-strategy ## Emailing Strategy - ### We will send two emails to each school - One email will be "treatment" (e.g. parent mention their child is transgender) and the other will be "control" (no mention) - We will randomize the order of the emails - Send at least one month apart - ### Sending two emails substantially increases statistical power --- name: regression-models ## Short regression model We will estimate a linear probability model (LPM) called the "short" model .tiny[.gray[(following Muralidharan, Romero & Wüthrich, 2019)]]: $$ `\begin{align*} PositiveResponse_{i} &= \beta_1 Black_{i} + \beta_2 Hispanic_{i} + \beta_3 Arab_{i} + \beta_4 LGT_i + \beta_5 Disability_i \\ &+ \beta_6 FemmeName_i + \beta_7 LowGrades_i + \beta_8 HighGrade_i + \beta_9 SESMD_i \\ &+ \beta_{10} SESPhD_i + EmailCongrols_i \beta_{11} + SchoolControls_i \beta_{12} + \epsilon_i \end{align*}` $$ Where `\(i\)` indexes each email: - `\(PositiveResponse_{i}\)` is a binary outcome variable for receiving a positive response - `\(Black_{i}\)`, `\(Hispanic_{i}\)`, and `\(Arab_{i}\)` are indicator variables for race and ethnicity - `\(LGT_i\)` is an indicator variable for lesbian, gay, trans, or non-binary students - `\(Disability_i\)` is an indicator variable for students with ADHD or autism - `\(FemmeName_i\)` is an indicator variable for a feminine name --- name: regression-models-continued ## Short regression model (continued) $$ `\begin{align*} PositiveResponse_{i} &= \beta_1 Black_{i} + \beta_2 Hispanic_{i} + \beta_3 Arab_{i} + \beta_4 LGT_i + \beta_5 Disability_i \\ &+ \beta_6 FemmeName_i + \beta_7 LowGrades_i + \beta_8 HighGrade_i + \beta_9 SESMD_i \\ &+ \beta_{10} SESPhD_i + EmailCongrols_i \beta_{11} + SchoolControls_s \beta_{12} + \epsilon_i \end{align*}` $$ Where `\(i\)` indexes each email and `\(s\)` indexes each school: - `\(LowGrades_i\)` and `\(HighGrades_i\)` are indicator variables for low and high academic achievement - `\(SESMD_i\)` and `\(SESPhD_i\)` are indicator variables for high socioeconomic status (SES) parents with MD or PhD degrees - `\(EmailControls_i\)` includes indicator variables for different randomized email features, and controls for email timing - `\(SchoolControls_s\)` which includes state fixed effects and school characteristics from the NLSD --- class: segue-yellow background-image: url("assets/TulaneLogo.svg") background-size: 20% background-position: 95% 95% count:false # Pilot <svg viewBox="0 0 640 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M624 448H16c-8.84 0-16 7.16-16 16v32c0 8.84 7.16 16 16 16h608c8.84 0 16-7.16 16-16v-32c0-8.84-7.16-16-16-16zM80.55 341.27c6.28 6.84 15.1 10.72 24.33 10.71l130.54-.18a65.62 65.62 0 0 0 29.64-7.12l290.96-147.65c26.74-13.57 50.71-32.94 67.02-58.31 18.31-28.48 20.3-49.09 13.07-63.65-7.21-14.57-24.74-25.27-58.25-27.45-29.85-1.94-59.54 5.92-86.28 19.48l-98.51 49.99-218.7-82.06a17.799 17.799 0 0 0-18-1.11L90.62 67.29c-10.67 5.41-13.25 19.65-5.17 28.53l156.22 98.1-103.21 52.38-72.35-36.47a17.804 17.804 0 0 0-16.07.02L9.91 230.22c-10.44 5.3-13.19 19.12-5.57 28.08l76.21 82.97z"></path></svg> --- name: main-results ## Overall Response and Positive Response Rates <img src="hadah-ed-audit-presentation_files/figure-html/bar-side-by-side-1.png" alt="" width="748px" style="display: block; margin: auto;" /> --- class: tulane-blue background-image: url(assets/TulaneLogo-white.svg) background-size: 260px background-position: 5% 95% count:false # Thank you! .pull-right[.pull-down[ <a href="mailto:hhadah@tulane.edu"> .white[<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M440 6.5L24 246.4c-34.4 19.9-31.1 70.8 5.7 85.9L144 379.6V464c0 46.4 59.2 65.5 86.6 28.6l43.8-59.1 111.9 46.2c5.9 2.4 12.1 3.6 18.3 3.6 8.2 0 16.3-2.1 23.6-6.2 12.8-7.2 21.6-20 23.9-34.5l59.4-387.2c6.1-40.1-36.9-68.8-71.5-48.9zM192 464v-64.6l36.6 15.1L192 464zm212.6-28.7l-153.8-63.5L391 169.5c10.7-15.5-9.5-33.5-23.7-21.2L155.8 332.6 48 288 464 48l-59.4 387.3z"></path></svg> hhadah@tulane.edu] </a> <a href="https://hussainhadah.com/"> .white[<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg> https://hussainhadah.com/] </a> <a href="https://github.com/hhadah"> .white[<svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg> @hhadah] </a> <br><br><br> ]]