A brief analysis of suspension rates in California public schools

Since I have heard more than a few complaints about disparities in school suspension rates, I thought I’d extend my prior analysis of data from California public schools to better understand the patterns here.

UPDATE: I realized after the fact that I botched the asian rate data a bit because California reports Filipinos as a separate group for some strange reason, i.e., they’re not included in the reported suspensions/numerator, and my denominator uses the normal federal/OMB definition, which includes doesn’t put filipinos in a separate category.   Filipinos are about 1/4th of the (federal) Asian category in CA schools and probably have a higher suspension rate than east asians (which is extremely low).  I don’t think it’d alter the between group differences all that much, especially not in ordinal terms, but I don’t feel like re-doing these all plots right now, so keep that in mind.

Out-of-school suspension rate (“(OOOS”) by district (weighted)

oos_boxplot_linearlte2

OOSS by district (weighted), y-axis as log-10

oos_boxplot_log10

Observation: There are clear racial/ethnic patterns here that cut across many different school districts.

OOSS by median family income

oos_by_mfi_binned_linear

OOSS by poverty rate

oos_by_pov_rate_linear

OOSS by education leveloos_boxplot_by_col_bin

oos_boxplot_by_col_bin_log_10

oos_scatter_by_mfi_linear

oos_scatter_mfi_log10

Observation: There appears to be a non-linear relationship between socioeconomic status and suspension rates.

Comparison with test scores

English Grade 9 w/ linear Y axis

oos_scatter_ela_g9_linear_y

English Grade 9 w/ log 10 y-axis (local polynomial trendline)

oos_scatter_ela_g9_log_y_loess

English Grade 9 w/ log 10 y-axis (linear trend line)

ela_scatter_g9

Test scores are generally a better predictor of suspension issues within and between groups than socioeconomic measures are.  In the table below I compared the strength of these various correlations for complete cases only, i.e., only districts with all of these measures available (to prevent, say, elementary school only districts from skewing the stats).

Microsoft Excel

oos_ela_g9_boxplot_binned_1SD

oss_boxplot_ela_g9_linear

Comparison of different reasons for suspension

oos_reasons_stacked_bar

os_reasons_totals

Despite some of the outliers below, we can pretty clearly see that there is a fairly strong linear relationship between violence and defiance.  Communities with higher rates of violence suspensions are apt to have similarly high rates of defiance suspensions.

oos_other_defiance_by_violence_non_injury
os_scatter_violence_vs_defiance

Microsoft Excel

The overall correlation across all of the above as separate items without grouping is 0.55.

Conclusion

I think it’s pretty unlikely that the reason blacks are suspended at disproportionately high rates is substantially the result of being unnecessarily suspended due to “cultural differences” or “racism” because:

1: The overall out-of-school suspension rates are well correlated with test scores, i.e., it “explains” much, if not quite all, of the between group differences (especially W-B).  Lower test scores predicts lower IQ, which predicts much increased behavioral problems, worse judgement, and so on.  Underperforming students are also less likely to be engaged in school and presumably have less to lose if they get suspended (or at least they may believe as much).

2: We see the same patterns in other (major) suspension categories, most of which are (arguably) more objective and more obviously “serious”.

3: We don’t see nearly the same problem with poor asians or poor latinos.  Lower income whites are actually suspended at higher rates than similarly low income latinos, which is much higher than low income asians (generally speaking).  If we’re not willing to presumptively label these differences the product of racism or bias, why should we presume otherwise for black-white differences?

4: These patterns are generally consistent across many different school districts.  This isn’t just a problem found in a few big cities or just in poor communities.


Extra Plots

oos_weapons_vs_violence oos_drugs_vs_violence oos_violence_vs_violence oos_other_by_violence


oos_smatrix_latino oos_smatrix_asian oos_smatrix_white oos_smatrix_black

2 thoughts on “A brief analysis of suspension rates in California public schools

  1. […] I am well aware that aggregating linearly correlated variables will tend to produce stronger correlations that you’d see with more granular data (e.g., state, county, family, individual, etc).  On the other hand, I am familiar enough with these statistics to know that you will see substantially weaker correlations between ethnic groups with other predictors.  Hispanics/latinos, for instance, tend to be worse off than than blacks by many economic measures, rarely appreciably better off, and yet their discipline problems are much less (even, interestingly, less than whites in CA controlling for median family income). […]

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