On Tuesday, the U.S. Department of Education (DOE) released the 2009-2010 civil rights data collection which tracks a number of equity indicators from schools around the country, everything from discipline rates to rates of sexual harassment, from schools around the country. We at NWLC were thrilled to see that the CRDC data has been cross tabulated by sex and race.
Cross tabu-what?
Let me digress. When data is collected, it can be disaggregated. That means that rather than just take a count of how many kids are suspended in a year, disaggregated data would count how many White kids and how many Native American kids are suspended in a year. Or you can disaggregate by sex and count how many girls and how many boys were subject to physical restraint in school. Cross tabulation takes that one step further and lets you look at one or more of these categories together.
Which is how we found out that 1 out of every 10 African American girls was subject to an out of school suspension last year. Boys made up about two-thirds of suspensions, but African American girls were more likely to be suspended than all other girls, White Boys, Hispanic boys, and Asian boys.
Over the past twenty-five years, there has been a lot of attention paid to the plight of African American men and boys in this country, and with good reason. Black men in the U.S. face shockingly high drop-out rates, unemployment rates and rates of incarceration. As Michelle Alexander has pointed out, there are currently more Black men in prison or on parole in this country than were enslaved before the Civil War began.
Unfortunately, the emphasis on the serious educational crisis for boys of color has resulted in little focus on the challenges facing girls of color. In fact, girls at risk — particularly girls of color — have alarmingly low graduation rates. Over 45% of Native American female students fail to graduate on time, if at all; the same is true for 38% of female African American and 39% of Latina students. Cross-tabulated data help us to ensure that problems faced by different subgroups of students are not masked, so educational interventions (or lack thereof) will be data driven, not based on stereotypes.