The Race to the SOL Bottom

Virginia’s economically disadvantaged (“ED”) students underperform their more affluent peers (“Not ED”) on the SOL tests; statewide, the pass rate difference is about 20%, depending on the subject. As a result, the raw SOL punishes divisions, such as Richmond, with relatively large ED populations.

So, in this look at Richmond’s place in the race to be the worst school division, let’s consider both the Not ED and the ED pass rates.

First, Reading: Here are the ten divisions with the worst Not ED pass rates.

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Here the Richmond Not ED pass rate fell by 2.2% but six other divisions managed to do worse. Petersburg, e.g., held it’s last place position with a decrease of 5.0%. Overall, Richmond improved from third to sixth from the bottom.

Notes: The “Division Averages” there are averages of the division pass rates, not the average of all Virginia students taking the tests. Some of the Halifax County data are absent from the 2019 download; I’m told that all the Halifax reading data were ED. In any case, Halifax is missing here..

As to the ED students, Richmond held on at second from worst.

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On the math tests (where a new, failure-averse scoring system improved pass rates statewide), the boost to Richmond’s Not ED rate was sufficiently feeble to drop the division from fifth to fourth worst.

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As well, despite the ED increase, Richmond slipped from fourth to third worst.

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For another view of Richmond’s performance, here is a graph of division reading pass rates v. the percentage of ED students taking the tests.


Richmond is the yellow points at 64.1% ED. The peer city, Norfolk, is the red points at 65.9% ED. (Remember, those are percentages in the tested population, not in the division overall.)

Richmond’s Not ED pass rate is 10.1 points, 1.6 standard deviations, below the fitted line. The ED rate is –18.2%, 2.2 standard deviations below the ED line.

An interesting aspect of this graph is the negative slope and nontrivial R-squared of the least squares fit to the Not ED pass rates while the R-squared value for the ED data is too small to imply any correlation. Said in English, it looks like the percentage of ED students shows a modest, negative correlation with the pass rates of their Not ED peers but not those of the ED students themselves.

The math data tell much the same story.


In this case, Richmond’s Not ED pass rate is 2.5 standard deviations below the fitted line while the ED is –1.8 SDs.

On both graphs, notice the peer jurisdiction outperforming Richmond notwithstanding ED populations in the same ballpark. Note also the divisions with ED populations larger than Richmond who, for the most part, manage to achieve higher pass rates.