Start 15 min til. (repeat 2-3 times) Thank you for logging on early. While you wait you will experience periods of silence. It’s 11am so we are going to get started.
Good morning I am George Triest, I am the director of the spptap, better known as spptap. This project is out of the NCOE funded by CDE, Special Ed division. Welcome! I’d like to Introduce Connie Silva-Brousard our technical assistance coordinator, who will take it from here.
Before we begin today I want to quickly give you a couple of reminders. First, this event is being recorded so if you experience any technical difficulties you will have another opportunity to view this webinar. Second, we will be sending out a very brief evaluation survey following this webinar. That will come to you through email so keep an eye out for it. As with past webinars, we have muted your telephone lines. If you have a question for today’s presenter please use chat to ask your question. If for someone reason chat isn’t working for you, please feel free to email your questions to firstname.lastname@example.org and we will make sure get an answer for you. Lastly, you will be asked to participate in a couple of polls, and as we transition from slide view to a poll, your screen will change.
I’d like to now introduce today’s speaker, Daniel Losen. Daniel Losen is a Senior Education Law and Policy Associate with The Civil Rights Project at UCLA and formerly a Lecturer on Law at Harvard Law School. He has authored numerous publications including the book “Racial Inequity in Special Education” and regularly provides guidance to policymakers, educators and advocates regarding the impact of law and policy on children of color and language minority students. Working under contract with the Wisconsin Department of Public Instruction, Mr. Losen developed the Annotated Checklist for Addressing Racial Disproportionality in Special Education. This asessment tool is the focus of Mr. Losen’s presentation today. Before becoming a specialist in education law and policy, Mr. Losen taught in public schools in Massachusetts for ten years and also helped found an alternative public school in Acton, MA.
SAY “THE DISTRICT’ NOT THEM.
Lenny at the Exploritorium Or is it Sam…it’s Sam Part of what we are asking districts to do is look at multiple connected factors. They might not be able to completely isolate each one, but they don’t need to. They do need to try see them more clearly and come up with ways to address one or more important ones.
WHEN I WORK WITH DISTRICTS I ALWAYS LOOK CLOSELY AT THEIR DATA FIRST AND PREPARE BY ANALYZING THE DISTRIC’TS DATA, OR AT LEAST OFFER ASSISTANCE
OK, now we are going to go to a poll. Next slide then switch to Poll mode.
The research suggests this could be the case in many districts. And it may also be true that poor and minority students are more likely to have inexperienced or poorly trained teachers (i.e. research on tracking has found this is often the case). We are on slide 14. THE NEXT SLIDE WILL CONTAIN TWO RELATED POLL QUESTIONS SO THERE WILL BE A PAUSE IN THE PPT WHILE WE TAKE THE POLL
OK AFTER THIS QUESTION THERE IS ANOTHER poll. AND AFTER THAT I’m reverting to the ppt and we’ll have a brief discussion about the results. Think about who gets labeled gifted and talented and which teachers teach those kids, or AP classes. Yes? No? And race of students? Yes? No? .
OK after poll I’m reverting to the ppt and we’ll have a brief discussion about the results. I’d encourage districts to look at this question, or something similar, even if they skipped it because of the research basis Yes? No? And race of students? Yes? No? .
Need to turn chat back on. We are on slide 17.
Pause for questions. WATCH TIMER and WAIT 30 seconds before responding and moving on to next slide.
On slide 20 FOR EXAMPLE, WELL TRAINED TEACHERS ARE A RESOURCE, TEACHER EXPECTATIONS AND HOW STUDENT PLACEMENTS ARE DETERMINED ARE POLICY CONSIDERATIONS. TIME FOR COLLABORATION…TIME IS A RESOURCE CONCERN, BUT CREATING THAT COLLABORATION OPPORTUNITY COULC B.
Example: If teachers know that nearly always kids labeled ED don’t spend much time in the classroom, that practice may contain a powerful incentive. Federal funds flow to students with IEPs. Sometimes state funds. But often no additional resources if a student is ONLY 504 eligible. Yet creating a 504 plan has some costs associated with it. The practice at a given school, probably unwritten, is that the teachers defer to the evaluators and the administrators. The opinions of parents and teachers may not be given much deference.
I ALSO PUT THE FEDERAL REQUIREMENTS IN THE ENDNOTES SO THAT ADMINISTRATORS CAN POINT OUT THAT THERE ARE FEDERAL REQUIREMENTS AND RESEARCH THAT SUPPORT OR REQUIRE PARTICULAR EXPLORATIONS AND EXAMINATIONS. SCHOOLS ARE REQUIRED BY THE STATUTE TO LOOK AT RACIAL DISPARITIES IN PLACEMENT AND DISCIPLINE AS WELL AS IN IDENTIFICATION STATES ARE REQUIRED TO LOOK AT POOR AND MINORITY CHILDREN’S ACCESS TO EXPERIENCED AND HIGHLY QUALIFIED TEACHERS
THE STATE IS REQUIRED TO ENSURE THAT DISTRICTS LOOK AT RACIAL DISPARITIES IN DISCIPLINE SUSPENSION: POLICY…I.E. suspension for bringing a cell phone to school, PRACTICE: using suspension frequently for all sorts of school code violations; PROCEDURE…coming.
I’m going to walk you through this example to illustrate the benefits of getting the district to look at their data over time and in creating simple graphs with their data. If I were working with district staff I’d have them do the risk, risk difference and risk ratio calculations themselves. You will get that chance later in this presentation. We are on slide number 25. I ALWAYS ENCOURAGE DISTRICTS TO LOOK AT THEIR SUSPENSION DATA. They are required to by law, but the disparities are often informative.
You would ask the district staff to make observations participants can offer about the trends you see in the risk for suspension in this district from 2004-2009? THIS TABLE SHOULD BE IN THE CALCULATION HANDOUT FILE. KEEP IT VISIBLE AS I’LL BE REFERENCING THESE DATA USE DRAWING TOOL In the next slide, based on my work with many districts, I review some typical observations some might offer. USE DRAWING TOOL TO HIGHLIGHT WHAT I’M TALKING ABOUT ASK THEM TO REFER TO THE PRINT OUT OF THIS TABLE …WAS AN ATTACHMENT
Here the point is to discuss how you should consider several analytical frames and look at trends over time. And you might find a tendency for the district to cast its data in the most positive light. Analyzing the trend data, annually, will be critical to evaluating the interventions the district decides to implement. What’s the true story? A: Risk ratio has gone dramatically down since 2004? B. Suspension risks have gone up more dramatically for Whites than Blacks since 2004? C. The Black/White discipline gap has nearly doubled in just 6 years, and Black’s with disabilities now experience an extraordinarily high risk for disciplinary exclusion? D. All the above?
EACH DISTRICT WILL LOOK DIFFERENT. SO YOU WOULD PROVIDE THIS ANALYSIS IN ADVANCE AND BE PREPARED TO DISCUSS WHAT YOU HAVE FOUND, BOTH POSITIVE AND NEGATIVE TRENDS.
Note: Some might criticize you for using phrases like, “extaordinarily high.” Caution is warranted because you don’t want to be too critical. I tend to use phrases like this only when I know the data are extraordinary. BUT IT’S IMPORTANT TO POINT OUT THE BIG PROBLEMS YOU FIND.
DRAW… I often create a work book , modified to fit the districts issues and data, with blank graphs that staff members can fill in to help them see the trends. Similar exercises can be used to demonstrate areas where the district is already showing some signs of improvement. I find it helpful to highlight some positive trends, to demonstrate that the district is likely already engaged in some effective activities and that you, as consultant, see those positive things, too. This was slide # 33.
When my son Sam came back from kindergarten one day…after about the first week of school… he told me, “ Daddy, today we learned the Pledge of illusions…. It ends with liberty and justice for none.
I think it’s important to raise the issue of implicit or unconscious racial and ethnic bias when working with a district. For many reasons…But it is also helpful to have these conversations in a manner that suggests societal responsibility. The issue is not whether this exists, nor that we need a Lady Gaga incubation and rebirth. But that acknowledging its existence helps staff take responsibility and meaningful action to reduce the impact….including regular discussions about the data showing racial and ethnic disparities.
We want to believe that we are helping children and making fair and objective decisions that is in the best interests of children. Most of the time that may be true. The data, however, present an uncomfortable alternative reality. Cognitive dissonance occurs when we find that the alternative explanation too difficult to except to acknowledge. Part of the goal then is to make it more acceptable to acknowledge that unconscious bias could be one of several contributing factors. Whether or not staff do any self-reflection, they may be less resistant to monitoring racial dispariites if they can acknowledge that bias may play a part.
You are on slide 40
Carrots? LENNY The flexibility in the use of the 15% for CEIS is also stick to many, but a carrot if used wisely.
The third prong raises additional issues like whether there had been a behavioral assessment and a behavioral improvement plan developed and implemented. These are IDEA requirements. So even though the main purpose of the checklist is to think beyond compliance, in some cases non-compliance with the IDEA could be a contributing factor. Discussing compliance is a delicate matter, especially where the goal is to help districts think about contributing factors in general education and not just focus on compliance with the IDEA.
Pause for questions. WATCH TIMER and WAIT 30 seconds before responding and moving on to next slide. I’ll respond and then we’ll move to checklist 3.
There are some districts that can legitimately show that environmental factors, or factors outside their control are responsible for the disproportionality in question. They are few because research suggests that usually multiple issues are at play. And in some cases where there concerns with factors such as lead exposure, schools can be part of the solution.
Lenny and Sam: Hopefully, districts will come to believe there are ways in which district policies, or practices, contribute. So by the time districts get to the third checklist, whether they are working with you directly on using the lists, or had reviewed them before your arrival, they aren’t as interested in blaming the disparities on external factors. But it always comes up…
This is slide 45 It represents a very common belief that warrants a response. Endnotes have a link to a presentation by Jack Jorgenson a special education director from Madison who un-packed this issue…and found only a minor impact.
I always do calculations like these before entering a district. The results invariably show that the identification rates are NOT the only areas of large racial disparities. In this example, educators IN the district are making the decisions to label children as “gifted” and to suspend children out of school. So, this suggests that district staff, do make decisions about students in the districts that yield large racial disparities in other areas. Often I lead with a slide like this because I want the district to consider a broad scope of solutions, including general education. Slide 50.
Yes poverty may correlate with higher risk for some disabilities, but poverty is not destiny. The size of the disparities that tend to get noticed are unlikely explained away by poverty. Class bias can have the same inappropriate affect as racial bias. Poverty also doesn’t explain large differences by gender, or the fact that in national data Blacks and Hispanics who are about equally poor, have very different patterns of special education identification.
Poor Blacks should have same risk as poor Whites…non-poor Blacks the same risk as non-poor Whites.
USE DRAWING TOOL TO HIGHLIGHT A AND B…
Slide 52 USE DRAWING TOOL
In this example 1/3 rd of the Blacks are poor, compared to just 1/5 th of the Whites. So to the extent poverty is a factor, it will affect Blacks more because a higher percentage are poor.
DISTRICTS PREFER GOOD NEWS. THERE IS NOT MUCH HERE. BUT I’D ACKNOWLEDGE (IF THE DATA SUPPORT IT) THAT POVERTY MAY HAVE AN IMPACT…BUT INVARIABLY IT CANNOT EXPLAIN THE DISPARITIES AWAY.
REMEMBER THAT EVEN IF POVERTY APPEARED TO EXPLAIN THE RACIAL DIFFERENCES, CLASS BIAS IF A FACTOR, IS CERTAINLY NOT APPROPRIATE.
It’s important to have the majority of the staff reject the status quo as unacceptable and acknowledge there are likely contributing factors under their control.
Data analysis to reject hypothesis, refine it or develop it further
1. Welcome Please Wait While Others Join the Meeting Connie Call-In 1-866-244-8528 Enter Pin 303385 and press # Today You Will Need Calculator Annotated Checklist for Addressing Racial Disproportionality in Special Education Calculation Handouts
2. Call-In 1-866-244-8528 Enter Pin 303385 and press # California Department of Education, Special Education Division's special project, State Performance Plan Technical Assistance Project (SPPTAP) is funded through a contract with the Napa County Office of Education. SPPTAP is funded from federal funds, (State Grants #H027A080116A) provided from the U.S. Department of Education Part B of the Individuals with Disabilities Education Act (IDEA). Opinions expressed herein are those of the authors and do not necessarily represent the position of the U.S. Department of Education. George Triest Connie Silva-Broussard SPPTAP
3. Reminders Recorded Follow-Up Survey Chat to Communicate [email_address] Respond to Polls
6. My Story…. <ul><li>2 nd Year Teaching </li></ul><ul><li>1/3 rd Students from Boston </li></ul><ul><li>1 Black male in particular was a handful. </li></ul><ul><li>Not mentally retarded (i.e. athletic talent and showed game smarts). </li></ul><ul><li>Re-evaluated: Waited for IQ score. </li></ul><ul><li>Would have been sent back to Boston as MR. </li></ul>
7. Every District is Different <ul><li>Checklists are built on research </li></ul><ul><li>Legal requirements </li></ul><ul><li>Refined by experience </li></ul><ul><li>Grouped to reflect different needs </li></ul><ul><li>Multiple causes of disproportionality </li></ul><ul><li>Concentrate on what schools can do. </li></ul><ul><li>Beyond compliance. </li></ul>
8. Using the Checklists to Formulate a Hypothesis and Suggest Remedies: <ul><li>List 1: District and School Resources </li></ul><ul><li>List 2: System Policy, Practice and Procedure Issues </li></ul><ul><li>List 3: Environmental factors </li></ul>
9. Multiple Reasons: Multiple Responses <ul><li>Research suggests multiple interconnected causes. </li></ul><ul><li>Finding just one cause is unlikely. </li></ul><ul><li>Selection of hypothesis: </li></ul><ul><ul><li>What the district can do. </li></ul></ul><ul><ul><li>Consider scope of contributing factors. </li></ul></ul>
10. Contributing Factors are Entangled
11. Use of Data With Checklist <ul><li>Broaden the inquiry </li></ul><ul><li>Find what is working as well as what isn’t working </li></ul><ul><li>Use simple measures to compare and track changes </li></ul><ul><li>Debunk common excuses </li></ul><ul><li>Track progress </li></ul><ul><li>Evaluate interventions </li></ul>
12. Checklist One: Resources <ul><li>Why resources? </li></ul><ul><li>Story of District A and needed support for new teachers. </li></ul><ul><li>Checklist helped them discover a likely factor and a likely remedy. </li></ul><ul><li>Important benefits from having regular and special educators at the table together. </li></ul>
13. Resources <ul><li>Teachers: </li></ul><ul><li>What the research says. </li></ul><ul><li>What the IDEA says. </li></ul><ul><li>What Title I says. </li></ul>
14. Do inexperienced or poorly trained teachers refer more students for evaluations? Your screen will change as I open voting.
15. <ul><li>Do districts think about whether the least experienced and qualified teachers tend to be placed with classrooms or in schools with higher numbers of poor and minority students? </li></ul>
16. <ul><li>Do they consider the support provided to less experienced teachers when they think about special education referral rates? </li></ul>
17. Discussion of Poll Results <ul><li>Why this question? </li></ul><ul><li>Research suggests that poorly supported and untrained teachers likely contribute to the phenomenon of disproportionality. </li></ul>
18. Required Use of 15% <ul><li>Rejects the status quo without raising compliance questions. </li></ul><ul><li>Prevention = $ spent in general education. </li></ul><ul><li>Should benefit the triggering racial subgroup. </li></ul>
19. General Education, Special Education and Discipline <ul><ul><ul><li>The National Research Council’s report suggests that difficult to manage minority students in the general education setting are removed via special education and more likely to be placed in restrictive settings. (research and legal citations are in endnotes). </li></ul></ul></ul><ul><ul><ul><li>Nationally, among students with disabilities, Blacks were over 3 times as likely as Whites to be suspended short term. </li></ul></ul></ul><ul><ul><ul><li>All relevant research citations are in the endnotes of each checklist. </li></ul></ul></ul>
20. Pause for Questions? Write your questions about checklist one in the chat area.
21. Issues Related to Resources <ul><li>You’ll see that the many issues related to resources reappear under checklist two, just the framing is slightly different. </li></ul>
22. Checklist Two: System policy, practice and procedure. <ul><li>Examine all policies: </li></ul><ul><ul><li>Tracking? </li></ul></ul><ul><ul><li>Inclusion? (are all teachers expected to be able to run an “inclusive” classroom?) </li></ul></ul><ul><ul><li>Response to intervention? </li></ul></ul><ul><ul><li>Time for collaboration? </li></ul></ul>
23. List Two: Practices <ul><li>Are there placement incentives? (ED = out of my room). </li></ul><ul><li>Power incentives? (i.e. deference to administration over parental or teacher input). </li></ul><ul><li>Test accountability incentives? </li></ul><ul><li>Unconscious bias? </li></ul><ul><li>Resource incentives? (IEP over 504) </li></ul>
24. List Two: Procedures <ul><li>How can teachers ask for help? </li></ul><ul><li>Fully implemented RTI? </li></ul><ul><li>Any consideration of classroom ecology? </li></ul>
25. Classroom Ecology? <ul><li>The IDEA requires that the dominant factor cannot be: </li></ul><ul><ul><li>ELL status or </li></ul></ul><ul><ul><li>an issue with reading </li></ul></ul><ul><ul><li>or math instruction. </li></ul></ul>
26. School Suspensions <ul><li>Look at links between identification; </li></ul><ul><li>restrictiveness of placement; </li></ul><ul><li>and discipline; </li></ul><ul><li>Does the district look at disaggregated data for school discipline? </li></ul><ul><li>Suspension: policy, practice and procedure. </li></ul>
27. Example of Calculations To Do With District:
28. Make sure folks at the district level understand risk calculations? <ul><li>You would review dividing the number of students in a racial group in a given category by their total enrollment. </li></ul><ul><li>You multiply that answer by 100 to get the “risk.” </li></ul><ul><li>The next slide shows the risk, risk differences and risk ratios. </li></ul>
29. How Does the District Interpret Their Own Data? Percent of Students With Disabilities Suspended first page located in calculation handout % OSS 2004 2005 2006 2007 2008 2009 Black 9 10 14 15 19 20 White 3 5 7 7 8 9 Risk Diff. +6 +5 +7 +8 +11 +11 Risk Ratio 3.0 2.0 2.0 2.1 2.4 2.2
30. Question <ul><li>Consider carefully the trends depicted on slide 29 </li></ul>first page located in calculation handout
31. What’s the true story? A. Risk ratio has gone dramatically down since 2004? B. Suspension risks have gone up more dramatically for Whites than Blacks since 2004? C. The Black/White discipline gap has nearly doubled in just 6 years, and Black students with disabilities now experience an extraordinarily high risk for disciplinary exclusion? D. All the above? refer to first page located in calculation handout
32. What best describes what’s happening to the children? <ul><li>A: True, the risk ratio went down from 3.0 to 2.2. </li></ul><ul><li>Generously acknowledge the truth of this observation, but ask whether risk ratio accurately describes what is happening. </li></ul><ul><li>Consider that 1 in 5 Blacks are now suspended when it had been 1 in 11 in 2004 (which is the frequency for Whites now). </li></ul><ul><li>Point out that focusing on risk ratio , alone, could mask the depth of the problem and its growth. </li></ul>
33. What best describes what’s happening to the children? <ul><li>B: True: Also acknowledge that the White risk went up 3 times their 2004 rate when they gained 6 percentage points. This was a larger “percentage” increase as Black risk went up 2.2 times their 2004 rate over the same period. </li></ul><ul><li>Consider that Blacks gained 5 whole percentage points more than Whites gained. </li></ul><ul><li>Percent growth over time can reflect the different starting points more than the absolute growth in the racial disparity. </li></ul>
34. What best describes what’s happening to the children? <ul><li>C. True: Blacks with disabilities, now experience an extraordinarily high risk for disciplinary exclusion. The Black/White difference is nearly double what it had been in 2004. “C” most accurately describes the trend, which is a growing gap, as well as the magnitude of the problem since dramatically more students with disabilities are being suspended. </li></ul><ul><li>The simple measures of “risk” and “risk difference” illustrate the racial disparities clearly. </li></ul><ul><li>Graphs using risk and risk difference can illustrate trends well. </li></ul>
35. Change in Risk for Suspension Since 2004
36. Don’t let the district take the pledge…
37. Implicit Bias Measurement <ul><li>Brain science – based on speed of positive and negative associations. </li></ul><ul><li>Implict Attitude Test (IAT) elicits unconscious attitude. </li></ul><ul><li>Implicit and explicit racial bias favoring whites exhibited by blacks and whites. </li></ul><ul><li>Data can help overcome bias…. </li></ul>
38. Practices: Implicit and Institutional Bias <ul><li>Unconscious Bias </li></ul><ul><li>Institutional Bias (my own experience and gender) </li></ul><ul><li>Reluctance to look at and discuss racial data. </li></ul><ul><li>Cognitive dissonance? </li></ul><ul><li>Preference to focus on a single factor because bias permeates the system. </li></ul>
39. Implicit/Unconscious Bias <ul><li>We don’t see or use all the evidence – </li></ul><ul><li>Measured through subtle, reflexive, unconscious types of behavior. </li></ul><ul><li>What we pay attention to matters. </li></ul>
40. Test Yourself www.implicit.harvard.edu
41. My Implicit Bias Ratings <ul><li>Twice: slightly negative toward Blacks. </li></ul><ul><li>Once: no bias. </li></ul><ul><li>Once: pro-Black bias. (after thinking about my civil rights and jazz heroes). </li></ul><ul><li>Context does matter! </li></ul>
42. Carrots and Sticks <ul><li>IDEA Non-compliance: The big stick. </li></ul><ul><li>Discipline is an area in special education where the disparity in “long-term” suspensions (over 10 days) may be linked to procedural non-compliance with the IDEA. </li></ul><ul><li>Endnotes for checklist has all the IDEA “sticks.” </li></ul>
43. Looking at data: <ul><li>Over time: are we improving? </li></ul><ul><li>Risk for suspension </li></ul><ul><li>Compare with other categories. </li></ul>
44. Do Principals Know The Law? <ul><li>Two districts in Delaware: </li></ul><ul><li>About 50% knew that students with disabilities had additional due-process rights </li></ul><ul><li>Manifestation determination: </li></ul><ul><ul><li>Behavior caused by disability, or </li></ul></ul><ul><ul><li>Resulted from failure to properly implement the IEP </li></ul></ul>
45. Pause for Questions? Write your questions about checklist two in the chat area.
46. Checklist Three: Environmental Factors <ul><li>Who is responsible? </li></ul><ul><li>What is the remedy? </li></ul><ul><li>Even when a causal factor lies outside the school, there are things schools can do. </li></ul><ul><li>Factors outside the school likely DO contribute…somewhat. </li></ul>
47. Whose Fault Is It? Alcatraz
48. They Were [Inappropriately] Identified Before They Entered <ul><li>Were the “suspect” new arrivals re-evaluated as required by law? </li></ul><ul><li>Was there really a net gain when you subtract those who left your district? </li></ul><ul><li>Have you run the numbers? </li></ul>
49. Environmental Factors <ul><li>If an outside factor is asserted as the primary cause, that hypothesis needs to be formulated fully and investigated. </li></ul><ul><li>Compare disparities in “Identification” with areas in which the district’s educators made all the decisions. </li></ul>
50. Patterns of Racial Disparity in District X 2006-2007 (U.S. Dept of Ed.)
51. Responses to Argument that Poverty is the Root Cause <ul><li>Poverty does not equal disability. </li></ul><ul><li>Labeling based on class differences is still inappropriate. </li></ul><ul><li>Disproportionality is NOT generally very large for low incidence less subjective categories. </li></ul><ul><li>HAVE THEY DONE THE MATH? </li></ul>
52. Calculator time…Imagine District A has Black/White Risk Ratio of 2.47
53. If Poverty Did Explain ALL the Difference….then…. <ul><li>Roughly equal rates among the poor and non-poor of all races. </li></ul><ul><li>Risk for poor of all races should be significantly higher than non-poor. </li></ul>
54. Poverty and SLD Identification Calculate the poor children’s risk for SLD by dividing B by A; and non- poor by dividing D by C. For each multiply the answer by 100. Put your answers in your table. A Free and Reduced Lunch Total Enrolled B FRL With SLD C Non-poor Enrolled D Non-poor with SLD # of Black 200 24 = B/A 400 47 =D/C # of White 200 12 = B/A 800 32 =D/C Risk Difference = = Risk Ratio = =
55. Poverty and SLD Identification AFTER RISK: Calculate the risk difference by subtracting White risk from Black risk. Calculate risk ratio by dividing Black risk by White risk. A Free and Reduced Lunch Total Enrolled B FRL With SLD C Non-poor Enrolled D Non-poor with SLD Total # of Black 200 24 = 400 47 = 71= 11.83 # of White 200 12 = 800 32 = 48 = 4.8 Risk Difference = = +7.03 Risk Ratio = = 2.47
56. Poverty and Identification: Results Free and Reduced Lunch Total Enrolled Poor = FRL With SLD Non-poor Enrolled Non-poor with SLD Black 200 24 = 12% 400 47 =11.75% White 200 12 = 6% 800 32 =4% Risk Difference = 6 points = 7.75 points Black to White Risk Ratio 2.0 2.94
57. What Did Poverty Explain? <ul><li>Without disaggregation the Black to White risk ratio had been 2.47. </li></ul><ul><li>Among the poor the Black/White risk ratio was just 2.0, considerably lower. </li></ul><ul><li>Many more poor Blacks than Whites. </li></ul><ul><li>Conclusion? </li></ul>
58. Poverty does NOT explain these racial disparities. <ul><li>Non-poor Blacks had almost the same risk as poor Blacks. But there was a large difference in risk between Non-poor and poor Whites. </li></ul><ul><li>Non-poor, Blacks were nearly three times more likely (2.94) to be labeled SLD than non-poor Whites and had an 8 percentage point gap! </li></ul><ul><li>Racial disparities were still quite large among the poor (2.0) and a 6 percentage point gap! </li></ul><ul><li>N on-poor Blacks were nearly twice as likely to be identified as having SLD as poor Whites . </li></ul>
59. Use Checklist to Encourage Reduction and Prevention <ul><li>“ Prevention” must include regular education & special education. </li></ul><ul><li>Real problem solving happens when districts reject the status quo and attempt to: </li></ul><ul><ul><li>get at root causes of racial disparities, </li></ul></ul><ul><ul><li>actively and regularly discuss their racial data with staff, </li></ul></ul><ul><ul><li>go beyond compliance, & </li></ul></ul><ul><ul><li>analyze more than those specific areas the district was selected for. </li></ul></ul>
60. Three Uses of Checklist <ul><li>Hypothesis: Forming hypothesis about contributing factors </li></ul><ul><li>Remedies: Ideally in combination with some data analysis to further develop the hypothesis (or reject it) and choosing remedies accordingly </li></ul><ul><li>Evaluation: Revaluating remedies continuously using multiple data sources (General and Special Ed.) </li></ul>
61. The End <ul><li>Further Questions or Consultation : Daniel J. Losen, M.Ed., J.D. Independent Consultant & Senior Education Law and Policy Associate The Civil Rights Project at UCLA (formerly at Harvard) </li></ul><ul><li>781-861-1222 </li></ul><ul><li>[email_address] </li></ul>