The State of Open Data on School Bullying
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How much of a problem is school bullying in NYC? The answer depends on who you ask. Data Clinic volunteers compared local surveys (where many students say bullying is happening) with federal data (where a majority of schools report zero incidents), to analyze these disparities for the 2013-14 school year. To present this work, the Data Clinic hosted an event as part of NYC’s Open Data Week, featuring a presentation of the analysis and a panel discussion with researchers, advocates, and journalists to better understand this important student safety issue.
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The State of Open Data on School Bullying
- 1. www.twosigma.com The state of open data on school bullying and harassment in NYC November 28, 2018 Two Sigma Data Clinic NYC Open Data Week March 6th, 2018
- 2. Important legal information November 28, 2018 2 The views expressed herein are not necessarily the views of Two Sigma Investments, LP or any of its affiliates (collectively, “Two Sigma”). The information presented herein is only for informational and educational purposes and is not an offer to sell or the solicitation of an offer to buy any securities or other instruments. Additionally, the information is not intended to provide, and should not be relied upon for investment, accounting, legal or tax advice. Two Sigma makes no representations, express or implied, regarding the accuracy or completeness of this information, and you accept all risks in relying on the above information for any purpose whatsoever. This presentation shall remain the property of Two Sigma and Two Sigma reserves the right to require the return of this presentation at any time. Copyright © 2018 TWO SIGMA INVESTMENTS, LP. All rights reserved.
- 3. November 28, 2018 est. 2014 pro-bono data and tech for social good 3
- 4. Open data on school bullying and harassment in NYC Navigating the landscape 4 CRDC CCD ED ATS OCR DASA NYC DOE VADIR NCES DBN NYS ED BEDS School Survey November 28, 2018
- 5. Open data on school bullying and harassment in NYC Federal 5 CRDC ED OCR • U.S. Department of Education (ED) • Office for Civil Rights (OCR) • Civil Rights Data Collection (CRDC) 95,507 schools nationwide November 28, 2018
- 6. Open data on school bullying and harassment in NYC Federal 6 Civil Rights Data Collection (CRDC) 2013-14 school year Allegations of Harassment or Bullying Students Disciplined for Harassment or Bullying Students Reported as Harassed or Bullied Race-, Sex-, Disability- based November 28, 2018
- 7. Open data on school bullying and harassment in NYC Local 7 NYC DOE • New York City Department of Education (NYCDOE) • NYC School Survey 1,784 schools citywide School Survey November 28, 2018
- 8. Open data on school bullying and harassment in NYC Local November 28, 2018 At my school students harass or bully other students. At my school students harass or bully each other based on differences … Students None of the time All of the time Parents At my child's school students harass or bully other students. At my child's school students harass or bully each other based on differences … Teachers At my school, students are often harassed or bullied in school. At my school, there are conflicts based on differences … Strongly Disagree Strongly Agree Strongly Disagree Strongly Agree+ Don’t Know NYC School Survey 2013-14 school year 8
- 9. Bringing federal and local together November 28, 2018 ? 9
- 10. Bringing federal and local together November 28, 2018 DBN NYC DOE School Survey Schools in the NYC School Survey are identified by a District Borough Number (DBN) … 10
- 11. Bringing federal and local together November 28, 2018 CRDC ED OCR 11 … while schools in the Office for Civil Rights’ Civil Rights Data Collection are identified by a 12-digit numeric ID called the “combokey”
- 12. Bringing federal and local together: what we didn’t do November 28, 2018 NYC School Survey Office for Civil Rights 12
- 13. Bringing federal and local together: what we did November 28, 2018 NYC DOE DBN BEDS NYC School Survey Office for Civil Rights NYC Open Data Portal: School Locations ATS ✔ ✘ 13
- 14. November 28, 2018 NYS ED BEDS NYC DOE DBN Local State CCD ED NCES Federal CRDC OCR 14
- 15. Bringing federal and local together: what we did November 28, 2018 Local (DBN) State (BEDS) Federal (NCESSCH) Federal (COMBOKEY) one school, many “unique” school IDs: 15
- 17. Open data on school bullying and harassment in NYC Federal + Local 17 CRDC CCD ED ATS OCR NYC DOE NCES DBN School Survey DASA VADIRNYS ED BEDS November 28, 2018
- 18. Open data on school bullying and harassment in NYC Local 18 CRDC CCD ED OCR NCES DASA VADIRNYS ED ATS NYC DOE DBN School Survey BEDS November 28, 2018
- 19. based on differences NYC School Survey 2013-14 school year November 28, 2018 At my school students harass or bully other students. At my school students harass or bully each other based on differences … Students Parents At my child's school students harass or bully other students. At my child's school students harass or bully each other based on differences … Teachers At my school, students are often harassed or bullied in school. At my school, there are conflicts based on differences … 19 bullying/harassment
- 20. NYC School Survey 2013-14 school year November 28, 2018 Students Parents Teachers bullying/harassment bullying/harassment based on differences None of the time All of the time Strongly Disagree Strongly Agree Strongly Disagree Strongly Agree+ Don’t Know 20 bullying/harassment bullying/harassment based on differences bullying/harassment bullying/harassment based on differences
- 21. 21November 28, 2018 Strongly Disagree/ None of the time Strongly Agree/ All of the time 35 Students bully/harass each other Students bully/harass each other based on differences 45 15 5 35 43 12 10 33 30 21 16 51 35 10 3 46 34 10 9 36 30 19 16 Parents’ “don’t know” responses not shown
- 22. Responses are highly correlated 22November 28, 2018 1.0 1.0 1.0 1.0 1.0 1.0 Higher correlation
- 23. NYC School Survey 2013-14 school year November 28, 2018 Students Parents Teachers bullying/harassment bullying/harassment based on differences None of the time All of the time Strongly Disagree Strongly Agree Strongly Disagree Strongly Agree+ Don’t Know 23 bullying/harassment bullying/harassment based on differences bullying/harassment bullying/harassment based on differences ✘1 4 1 4 1 4
- 24. NYC School Survey Creating a common scale for comparing schools to each other November 28, 2018 24 Average school “score” = 1.73 1 4321 432 43 46 6 5
- 25. NYC School Survey Creating a common scale for comparing schools to the citywide average November 28, 2018 25 1 2 Given the average school “score” for each school… Calculate the citywide school “score” Compare each school’s “score” to the citywide average We do this for both bullying/harassment questions - Parents - Students - Teachers 1 432 average school “score” 1.73 average NYC “score” 1.96 school “z- score” -0.72
- 26. 26November 28, 2018 z-scores students 2.56 -2.28 z-scores 0.10 average Bullying/harassment based on differences: student responses
- 27. 27November 28, 2018 z-scores parents 2.33 -2.43 z-scores -0.09 average Bullying/harassment based on differences: parent responses
- 28. 28November 28, 2018 z-scores teachers 3.10 -1.91 z-scores -0.23 average Bullying/harassment based on differences: teacher responses
- 29. Teachers and students appear to disagree in the largest and smallest schools 29November 28, 2018 School enrollmentLower Higher Teachers feel more strongly Students feel more strongly Feelings about the prevalence of bullying/harassment no difference
- 30. Open data on school bullying and harassment in NYC Federal 30 CRDC ED CCD NCES OCR ATS NYC DOE DBN School Survey DASA VADIRNYS ED BEDS November 28, 2018
- 31. Open data on school bullying and harassment in NYC Federal 31 Civil Rights Data Collection (CRDC) 2013-14 school year Allegations of Harassment or Bullying Students Disciplined for Harassment or Bullying Students Reported as Harassed or Bullied Race-, Sex-, Disability- based November 28, 2018
- 32. Civil Rights Data Collection Office for Civil Rights 2013-14 school year November 28, 2018 • Sex-based bullying/harassment is the most commonly alleged category, disability-based is the least • 75% of NYC schools report zero allegations (of any type) of bullying/harassment to the federal OCR. Nationally, this number is 80%. 32 one zero multiple # of schools reporting ________ allegations of bulling/harassment 1314 268 158 0 at least 1
- 33. Characteristics of schools with … 33November 28, 2018 0 allegations Total Enrollment 576 ? 1+ allegations Students with disabilities (%) English Language Learners (%) 713 18 19 14 12 Additional characteristics not shown as there were no significant differences. *z-scores are shown for the bullying/harassment due to differences question (results for responses the general question were similar) Parent responses z-scores* -0.12 0.37 Student responses z-scores* -0.15 0.27 Teacher responses z-scores* -0.15 0.45 1314 schools (75%) reporting 0 allegations 426 schools reporting 1+ allegations
- 34. each line is a school How much do the two surveys (dis)agree? 34November 28, 2018 ? % of students who say bullying/ harassment happens all of the time in … • Schools that reported at least 1 allegation • Schools that reported 0 allegations
- 35. agreement disagreement Zones of (dis)agreement 35November 28, 2018 ? high perception of bullying/ harassment based on differences low perception at least one allegation zero allegations axis represents square-root of allegations
- 36. Which factors are associated with survey disagreement? 36November 28, 2018 ?High Schools vs. Elementary Schools Parents Students Teachers High Schools vs. Middle Schools High Schools vs. Mixed-Grade Schools General Education Schools vs. Career/Technical/etc. Schools Regular Schools vs. Charter Schools Total Enrollment Female (%) Black (%) Hispanic (%) Students with Disabilities (%) English Language Learners (%) Free Lunch (%) High Schools vs. Elementary Schools High Schools vs. Middle Schools High Schools vs. Mixed-Grade Schools General Education Schools vs. Career/Technical/etc. Schools Regular Schools vs. Charter Schools Total Enrollment Female (%) Black (%) Hispanic (%) Students with Disabilities (%) English Language Learners (%) Free Lunch (%) High Schools vs. Elementary Schools High Schools vs. Middle Schools High Schools vs. Mixed-Grade Schools General Education Schools vs. Career/Technical/etc. Schools Regular Schools vs. Charter Schools Total Enrollment Female (%) Black (%) Hispanic (%) Students with Disabilities (%) English Language Learners (%) Free Lunch (%) not significantly associated with OCR-NYC School Survey (dis)agreement associated with OCR-NYC School Survey disagreement
- 37. We learned that … November 28, 2018 37 • There are several types of school IDs, at the local-, state-, and federal- levels: → DBN = “District Borough Number” → ATS = “Automate the Schools” → BEDS = “Basic Education Data System” → NCESSCH = “National Center of Education Statistics School ID” • Teachers’ responses are less correlated with students’ and parents’. This varies by school enrollment • In aggregate, perceptions of school bullying/harassment are related to the federal reporting of bullying/harassment • But perceptions can vary dramatically, even in schools that report zero allegations—which is the vast majority of schools • Bigger schools tend to have more disagreement between local and federal school surveys
- 38. 38November 28, 2018 DataClinicInfo@twosigma.com Rachael Weiss Riley & Christine Zhang Dave Santin Tiffany Chang Chris Mulligan special thanks to: Ben Wellington (Two Sigma), Erin Stein (Overdeck Family Foundation), Matt Chingos & Erica Blom (Urban Institute), Adrienne Schmoeker (NYC MODA), Nick Chmura & Two Sigma Q4 2017 Hack Day participants
- 39. 39November 28, 2018 Julia Bloom-Weltman Director of Research Applied Engineering Management Meghan McCormick Research Associate MDRC Johanna Miller Advocacy Director New York Civil Liberties Union Jasmine Soltani Data Manager Research Alliance for NYC Schools Amy Zimmer Journalist, Content Strategist Localize.city
Notes de l'éditeur
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- The Two Sigma Data Clinic harnesses the power of data and technology to help nonprofits have greater impact on the communities they serve. Our team of data scientists and engineers donate time and analytic expertise to help nonprofits understand and use their own data more effectively.
- Section I: intro to the open data landscape, challenges we faced in navigating it, etc. These may seem like alphabet soup/blobs of text/unconnected nodes, but by the end of this talk you’ll see what they mean
- https://surveys.nces.ed.gov/crdc/UserAccount/Login?ReturnUrl=%2Fcrdc%2F The purpose of the U.S. Department of Education (ED) Civil Rights Data Collection (CRDC) is to obtain data related to the nation's public school districts and elementary and secondary schools’ obligation to provide equal educational opportunity. To fulfill this goal, the CRDC collects a variety of information, including student enrollment and educational programs and services data that are disaggregated by race/ethnicity, sex, limited English proficiency, and disability. The CRDC is a longstanding and important aspect of ED’s Office for Civil Rights overall strategy for administering and enforcing the civil rights statutes for which it is responsible. This information is also used by other ED offices as well as policymakers and researchers outside of ED. The CRDC is a mandatory data collection, authorized under the statutes and regulations implementing Title VI of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, Section 504 of the Rehabilitation Act of 1973, and under the Department of Education Organization Act (20 U.S.C. § 3413). The regulations implementing these provisions can be found at 34 CFR 100.6(b); 34 CFR 106.71; and 34 CFR 104.61.
- Students in grades 6-12 answer the survey “differences (such as race, color, ethnicity, national origin, citizenship/immigration status, religion, gender, gender identity, gender expression, sexual orientation, disability or weight).”
- Code modified from https://rosettacode.org/wiki/Levenshtein_distance#Python Other “PS 290” schools in NYC: PS 290 Manhattan New School, PS 290 Juan Morel Campus
- https://data.cityofnewyork.us/Education/2013-2014-School-Locations/ac4n-c5re
- https://data.cityofnewyork.us/Education/2013-2014-School-Locations/ac4n-c5re
- https://www.dnainfo.com/new-york/20150909/rego-park/how-navigate-citys-murky-system-for-tracking-bullying-schools
- Our focus in this presentation. Begin Section II: some descriptive stats, methodology
- Students in grades 6-12 answer the survey “differences (such as race, color, ethnicity, national origin, citizenship/immigration status, religion, gender, gender identity, gender expression, sexual orientation, disability or weight).”
- Students in grades 6-12 answer the survey “differences (such as race, color, ethnicity, national origin, citizenship/immigration status, religion, gender, gender identity, gender expression, sexual orientation, disability or weight).”
- http://annkemery.com/agree-disagree-scales/ Likert descriptives notebook
- In general there is a fairly high, positive correlation between all the questions (darker = more) A variable is correlated with itself Students more correlated with students, etc. (blue boxes) Within the surveyed population the two questions are most correlated – e.g., students (dark blue box) And between students and parents we see some pretty strong correlations (box to left of dark blue box) But correlations are lower between students and teachers as well as between parents and teachers (bottom boxes)
- Students in grades 6-12 answer the survey “differences (such as race, color, ethnicity, national origin, citizenship/immigration status, religion, gender, gender identity, gender expression, sexual orientation, disability or weight).”
- Example is Bronx High School of Science. We do this for students, teachers, parents for each question
- Example is Bronx High School of Science. Standardized comparison We do this for students, teachers, parents for each question
- If there is perfect agreement, it would be a horizontal line Scatter notebook
- https://surveys.nces.ed.gov/crdc/UserAccount/Login?ReturnUrl=%2Fcrdc%2F The purpose of the U.S. Department of Education (ED) Civil Rights Data Collection (CRDC) is to obtain data related to the nation's public school districts and elementary and secondary schools’ obligation to provide equal educational opportunity. To fulfill this goal, the CRDC collects a variety of information, including student enrollment and educational programs and services data that are disaggregated by race/ethnicity, sex, limited English proficiency, and disability. The CRDC is a longstanding and important aspect of ED’s Office for Civil Rights overall strategy for administering and enforcing the civil rights statutes for which it is responsible. This information is also used by other ED offices as well as policymakers and researchers outside of ED. The CRDC is a mandatory data collection, authorized under the statutes and regulations implementing Title VI of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, Section 504 of the Rehabilitation Act of 1973, and under the Department of Education Organization Act (20 U.S.C. § 3413). The regulations implementing these provisions can be found at 34 CFR 100.6(b); 34 CFR 106.71; and 34 CFR 104.61.
- The top 10 schools form ~30% of the total sex-based allegations Binary classification Ocr descriptives notebook Also descriptive stuff notebook
- Scatter notebook
- Pull out the 2 examples of outliers
- For example - 75% of schools have 0 allegations; 25% have 1 or more allegations - So, we take a look at the (bottom) 75th & (top) 25th percentile of scores for parents/students/teachers - For instance, students on the harass/bully based on differences question What is the threshold/cutoff z-score of the bottom 75% of schools? 0.70614: 75% of schools are below this #, and 25% are above. Then, we look at each school’s z-score. If it’s lower than 0.7061 we say it’s 0 (“low” bullying/harassment) and if it’s higher than 0.7061 we say it’s 1 (“high” bullying/harassment) When allegations are 0 and the school is 0 (low-low) then this is agreement Same for when allegations are 1+ and the school is 1 (high-high) Otherwise, it’s disagreement Scatter notebook
- First show a list of all variables Then show everything (parents, etc.) Then show grey color change + arrows Highlight enrollment Among all three logistic models … enrollment matters
- Include a crosswalk!
- Hold questions until end of panel discussion.