Attendance. And Not.

The 2018 Superintendent’s Annual Report has the dropout numbers.  Combining those data with the September 30 head count, we see that Richmond is the runaway leader in dropouts.

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Those 517 dropouts in Richmond look less appalling when expressed as a percentage because most of the dropouts come in the later grades.  (Richmond’s 4-year cohort dropout rate in 2018 was 20.2%.)

It is perhaps more revealing to compare these percentages.

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Or, in terms of a graph,

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That Richmond rate is 3.99 times the state average.

Our Leaders, however, are shouting “Nolo Problemo!”  Last year our Generous Assembly gutted the mandatory attendance laws; Richmond is celebrating by firing its attendance officers.

Your tax dollars at “work.”

Is Marriage Good for Schools?

Having been enticed by the 2017 census data, I turned from the “female householder, no husband present” data to the “married couple families” numbers.

Notes: The census table does not include data for the two towns that have independent school divisions, Colonial Beach and West Point.  Presumably those data are included in the reports for the surrounding counties; I don’t have a way to correct for that (other than by leaving out the counties, which I didn’t do).  VDOE reports consolidated SOL data for Emporia/Greensville County, Fairfax City/County, and Williamsburg/James City County under the latter jurisdiction in each case; I’ve summed the census data for each pair and reported the joint average.

Let’s start with reading.

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Not only did we get a two-digit R-squared, for a change, but one that is robust: Division reading SOL pass rates are strongly associated here (ρ = +0.68) with the percentage of married couple families.

Of course, the correlation does not tell us about causation.  Indeed, it is likely that other factors drive both sets of numbers. 

That caveat aside, we again see Richmond (the gold square) underperforming substantially while the peer jurisdictions (the red diamonds, from the left Norfolk, Newport News, and Hampton) are near or above the fitted line.  (As a courtesy to both of my readers, the purple diamond is Lynchburg, the green, Charles City.)

For a closer look at Richmond’s marital neighborhood, here is the same graph, expanded to show only the jurisdictions with <65% married couples.

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The fitted line is for the entire dataset.

The math scores tell the same story (with Richmond underperforming even more dramatically).

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As with the “female householder” dataset, the married couple SOL data also show suggestive correlations with both the economically disadvantaged (“ED”) and the more affluent (“Not ED”) students’ performance.

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(In the second graph of each pair, only the ED points are labeled.  Look directly above those points – same % married – to find the corresponding Not ED points.)

Indeed, the fits to the Not ED group are substantially more robust than to the ED students, showing where marriage or the underlying factors that affect both marriage rates and SOL pass rates has/have stronger effects.

As in the single parent case, these data tell us:

  1. The raw SOL pass rates punish a division for poverty and even more for families without married couples; and
  2. Even with the pass rates corrected for the effects of both larger populations of ED students and lower populations of married couples, the Richmond schools underperform.  Appallingly.

Needed: A Lot of Good Men

We have seen that “economically disadvantaged” (“ED”) students generally underperform their more affluent peers (“Not ED”) on the SOL tests. 

The natural consequence of that is that divisions with more ED students generally deliver lower pass rates.  Less obviously, as the percentage of ED students increases, the pass rates of the Not ED students decrease while those of the ED students are only slightly lowered.  For instance:

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There is a lot of scatter in those data.  Indeed, the only robust correlation is in the all-student division average rates, where the effect of increasing numbers of ED students is to be expected.

Looking for other factors that might have more predictive effect, let’s turn to the census data showing numbers of “female householder, no husband present” families in the Virginia jurisdictions.  The latest data there are for 2017.

To start, here are the division average pass rates on the 2017 reading tests v. the no-husband percentages:

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Notes: The census data do not include Colonial Beach and West Point, both of which have independent school districts; their census data probably are subsumed in reports for the counties that include those towns.  The gold square on the graph is Richmond; the red diamonds are the peer cities, from the left Newport News, Hampton, and Norfolk; the green is Charles City; purple, Lynchburg.

Whew!  This is much more dramatic: The ED graph (2018 data) has a slope of –2.8 % per 10% increase in the Ed population.  Here (2017 data) we see a slope of nearly -6.4% for a 10% increase in the no-husband population.  The fitted line of the ED SOL graph extrapolates to a pass rate of 63.3% at 100% ED; the no-husband graph extrapolates to a pass rate of 25.7 at 100% no-husband households.

For a look at the divisions with a tougher job, here is the no-husband graph with only the high percentage divisions shown (the fitted line is for the entire dataset).

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The math data tell much the same story.

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Take a bow, ghost of Secretary Moynihan.

Taking a further step, here are the reading data broken out for the ED and the Not ED students.

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The ED data extrapolate to 29.8% at 100% no-husband households; the Not ED extrapolation gives 50.2%.

Looking just at the >25% no-husband divisions:

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Note: The second graph is too busy as it is so I’ve left the labels off the ED series.  You can identify the points there by looking for the labeled Not ED points directly above (i.e., same % no-husband).

Recalling that correlation does not imply causation, we cannot say that the missing husbands are the cause of these effects.  We can say that both ED and Not ED pass rates are generally lower in divisions with larger percentages of female parent homes and that the effect is nearly the same for both ED and Not ED students.  As well, the absence of the husband predicts over a fifth of the variance (statistic-speak for scatter from the fitted line).

Richmond, as usual, is underperforming. 

(Darn!  Another excuse that’s available to RPS only if they’re willing to lie.)

The math data sing a variation on the same theme.

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We can draw at least two conclusions:

  1. As with the ED population, the relationship of SOL test results to the number of no-husband households shows that the raw SOL pass rate is a defective standard for measuring division academic performance.  Said more succinctly: The SOL measure punishes a division for poverty and, still more powerfully, for single parenthood in its student base.
  2. Even with the pass rates corrected for effects of the large ED and no-husband populations, Richmond schools underperform.  Atrociously.

What Funding Gap?

The estimable Jim Bacon points to a study of school spending by state.  He concludes: “In Virginia, districts that serve mostly black students spend about $200 more per student on average.”

Well, please recall what Mark Twain said about statistics.

Please also notice that the study was prepared by EdBuild, which advocates for school funding and is funded in part by the Gates FoundationAnother study (with, obviously, a different viewpoint) asserts that of 2,625 political contributions by staff of Gates grantees, only 6 went to Republicans. 

In this context, we can wonder about the methodology of the EdBuild study: The study compared funding of “nonwhite” districts – those with more than 75% nonwhite students – with “white” districts – those with more than 75% white students.  The study does not explain the basis of the 75% criterion; it does not report the results of choosing other criteria; it does not mention local costs of living.

(Indeed, ± 75% is very close to ± 1.2 standard deviations; if there had been a statistical basis for the study, we might have expected to see a 68% or a 95% criterion.)

Thus, it is hard to know exactly what the study shows, albeit it seems to give Virginia some modest bragging rights.

There is a Virginia data set that can shed some light on the matter.  The Superintendent’s Annual Report for 2017 (the latest available data) provides at Table 13 disbursement data for each division.  I’ve extracted the day school (school operations not including food, adult ed., pre-K, etc.) expenditure per student.  The Fall Membership Report database provides the 2017 enrollments for students of all races and for “white, not of Hispanic origin” students, inter alia

If we graph the day school expenditure v. the percentage of nonwhite students, we obtain:

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Of course, correlation does not imply causation (another thing the EdBuild study does not mention) but the absence of correlation does tell us to look elsewhere for causes.  Here, 93% of the variance (that’s statspeak for “scatter”) comes from factors other than the percentage of nonwhite students.

In any case, the least squares fit offers the same result as an eyeball examination: There’s LOTS of scatter but the divisions with larger nonwhite populations are not being punished.  So, modest (6.6%) bragging rights.

Looking at the data we also see that the EdBuild average being pulled up by the older, urban divisions with large nonwhite populations and with higher costs of living (with the notable exceptions of Petersburg, which has a reputation for being notoriously impoverished, and Sussex, which is decidedly non-urban).

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Among those divisions, the R-squared rises to 9%.

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At the other end of the spectrum, the low expenditure divisions are mostly rural counties with relatively lower costs of living.

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The Big spenders here are Bath (38% of the budget is VEPCO money), Highland (43% of budget from property taxes), and Rappahannock (who knows?).

Interesting, perhaps.  It might also be interesting to look at the expenditures corrected for cost of living. 

In any case, no racial funding gap on the expenditures.

With all that said, it remains that, while school finances are important to the teachers and the schools’ bureaucrats, they are irrelevant to student performance among the Virginia divisions, e.g.,

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Note: These are total disbursements, not just day school.  Richmond is the gold square; the peer cities Hampton, Newport News, and Norfolk, the red diamonds; Lynchburg, blue; Charles City, green.

Serving the Numbers, Not the Students

With the aid of our General Assembly, Richmond has abandoned its truant students in order to improve its numbers.

We are reminded by a piece on NPR that you can’t teach students who don’t attend school. 

The General Assembly noticed that problem awhile back.  In 1999, they amended Code § 22.1-258 to install requirements for truancy responses:

  • Any unexcused absence: Contact with the parent;
  • 5 unexcused absences: Attendance Plan;
  • 6 unexcused absences: Conference with Parents;
  • 7 unexcused absences: Prosecute parents or file CHINS petition.

That was massively unpopular with our public school bureaucracy.  The Board of “Education” responded by requiring the divisions to report the number of students for whom a conference was scheduled and the aggregate daily attendance.  Notwithstanding its duty and authority “to see that the [mandatory attendance laws] are properly enforced throughout the Commonwealth” the Board cheerfully ignored the other requirements of the statute.

Richmond followed that lead.  After ten absences they sent the parents a letter.  They did very little else, even as their truancy rate exploded.

In 2018, the Generous Assembly amended § 22.1-258 to gut the enforcement mechanism: Now after ten unexcused absences, the attendance officer may prosecute the parents or file a CHINS petition.  The attendance officer is no longer responsible for the five- and six-absence plans and conferences.

Richmond is responding by firing all its seventeen attendance officers and replacing them with seven “attendance liaisons.”

(The statute still provides that “[w]here no attendance officer is appointed by the School Board, the division superintendent or his designee shall act as attendance officer.”  Presumably these “liaisons” now will be the superintendent-designated attendance officers.)

On the 2017 data, 4,998 Richmond students had ten or more unexcused absences.  That’s 294 per attendance officer. 

Who can think that the truancy situation will improve with “liaisons” who should have, on those data, 714 cases each?  But, of course, those “liaisons” don’t have to actually do anything so we might wonder why we’re paying even for seven.

(BTW: At the old limit of seven, there were 7,234 students with 7 or more unexcused absences in Richmond in 2017.  That would be 1,033 per “liaison” if they were actually dealing with truancy.)

We don’t have to dig far to unearth the reasons for this deliberate disservice to schoolchildren: Students who are not in school can’t be taught.  Students who are truant frequently drop out.  Students who have dropped out cannot lower the SOL pass rates.  Indeed, if the division can get rid of these troublesome children in middle school, they won’t even count against the cohort graduation rate.

This is win/win for the schools and the Board of “Education.”  Never mind those inconvenient children.

Mendacious Excuse, II

Having sentenced myself to read the School Board’s no-longer-secret (but probably still illegal) budget, I moved on from Page 11 and was stopped at page 12 by a further false excuse for Richmond’s lousy (and very expensive) performance:

Special Education Students

Another factor for consideration in educating the students residing in the City of Richmond is that approximately 4,100 or 17.5% of our students qualify for special education services. The graph shown below represents the percentage of special education students benched against state-wide averages and surrounding districts; RPS = 17.5%, state average = 13.0%.

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This graph is a step up from the one on p.11 that stopped at 2014: This one goes to 2018, albeit the database continues to 2019. 

As well, this page again calls Norfolk a “surrounding district.” 

More to the point, here is my graph for Richmond and the peer districts.

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You may have noticed that the Board’s Richmond numbers and mine agree only for 2016.  Either the database has been heavily amended since the Board pulled its data or the Board has miscalculated.

Still more to the point, this appears to be another official embrace of a “Blame the Students” excuse for the School Board’s own failure. 

It is clear, of course, that disabled students underperform their more abled peers.  On the SOL pass rate, the state average difference ranges from just over thirty to over forty points, depending on the subject.

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But Richmond magnifies that effect: Because of the awful schools, Richmond’s students, economically disadvantaged and not, grossly underperform their peers.  For example, on the reading tests Richmond’s disabled students underperformed eight of the ten divisions with larger disabled populations and Richmond’s non-disabled students underperformed all ten of those divisions (Richmond is the enlarged, gold points):

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On the math tests, it was nine of ten and, again, all ten.

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For the School Board to blame those disabled students for its own costly failures is a shameless lie.

Our Neighbor, Norfolk

Following the kerfuffle over our School Board’s’ (probably illegal) secret adoption of its 2020 budget, the Board released that budget.

I have a lot of reading to go, but was stopped by this on page 11 of the budget:

Free and Reduced Lunch Population

Free  and  reduced  lunch  population  is  a  measure  of  poverty.  As  reflected  in  the  Department  of  Education’s October 31, 2013 report, RPS ranked as the 9th highest free and reduced lunch population in the  Commonwealth  with  17,351  or  over  74.25%  of  our  students  receiving  subsidized  meals  under  the  Federal  school  lunch  program.  The  graph  shown  below  depicts  Richmond’s  status  as  compared  to  neighboring districts and the state average.

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Norfolk is 92 miles away by car.  Some “neighboring district.”

Then we have the dates: The graph stops at 2014.  The “Program Statistics” page on the VDOE Web site has Free/Reduced Lunch data thru 2018-2019.

Even more to the point, VDOE has a more general measure of poverty, “economically disadvantaged.”

Economically Disadvantaged   A flag that identifies students as economically disadvantaged if they meet any one of the following: 1) is eligible for Free/Reduced Meals, or 2) receives TANF, or 3) is eligible for Medicaid, or 4) identified as either Migrant or experiencing Homelessness.

The VDOE Fall Membership database provides the economically disadvantaged populations through 2018-19 for the state and all divisions.  Here are those data for Richmond and the peer jurisdictions:

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Do you suppose the School Board’s graph stopped at 2014 because they were just too lazy to update the graph?  Or, perhaps, because that was the year that showed Richmond’s largest free/reduced percentage?

Still more to the point, this appears to be an official embrace of the School Board’s “Blame the Students” excuse for its own failure. 

It is clear, of course, that economically disadvantaged students underperform their more affluent peers.  On the SOL pass rate, the state average difference is about 20 points, depending on the subject. 

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But Richmond magnifies that effect: Because of the awful schools, Richmond’s students, economically disadvantaged and not, grossly underperform their peers.  For example, on the reading tests (Richmond is the enlarged, gold points):

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Note added 2/28: That’s %ED in the tested group, not the division.

For the School Board to blame poverty for its own failures is a shameless lie.

It begins to look like reading this budget will be about as much fun as reviewing the performance of Richmond’s schools.

Problem in Paradise: Theft from Motor Vehicle in Forest Hill

The daffodils are budding in the alley and I still haven’t updated the Forest Hill crime report data.  Let’s get to work.

First the geography: In the Police Dept. database, the neighborhood runs from the park to the Boulevard and from Forest Hill Ave. to the river:

As you see, this does not include all of the Forest Hill Neighborhood Ass’n area and does include some of the Westover Hills Ass’n area.  It includes only one side of Forest Hill Ave, notably only one side of the commercial area.

Microsoft has a nice view of the area.

For the period from the start of the Police Department Database, January 1, 2000, through December 31, 2018, that database contains 3,081 offense reports for the Forest Hill neighborhood. 

The database contains lots of duplicates.  In this case, 999 of the entries duplicate the incident number, offense code, and offense number of another incident, leaving 2,082 unique entries.

Among that 2,082 entries, “theft from motor vehicle” is the most common at 27%.

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I like to call those incidents “car breakins” but that is not accurate: Most of those are cases where park visitors left the car unlocked.  The count of “Destruction property/private property” incidents gives a high but approximate measure of the actual breakins.  “Abandoned property in car” might be more accurate.

As usual in a quiet neighborhood, most of the incidents involve property crime.  In the present case, the most frequent violent crime is simple assault, in tenth place behind 69% of the total (ninth place, 67%, if we don’t count the 56 natural deaths).

The neighborhood was enjoying a consistent pattern of improvement until 2015.

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The increases then were driven by increases in theft from motor vehicle.

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By far our worst block for crime is 4200 Riverside Drive.

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That block is home to the 42d St. Parking Lot.

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Half of the crime reported in the block is theft from motor vehicle, with second place going to the property destruction where the thief had to break in because the car was locked.

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No telling how much of the rest is spillover from the criminals lured into our neighborhood by the unlocked cars.

The earlier decreases in the 4200 block came after Parks’ 2005 response to neighborhood complaints: They started locking the gates to the 42d. St. lot at night and off season and they installed rocks to block parking in the part of the lot that is less visible from the street.

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I attribute the recent increases to the increased use of the Park, the removal of the rocks in 2016, and the reassignment of Stacy, the bicycle cop.

Aside from 4400 Forest Hill (mostly the nursing home) and 4700-4800 Forest Hill (the commercial area), the other blocks at the top of the list are high theft from motor vehicle blocks:

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There are two lessons here:

  • Leaving stuff in the car, especially in an unlocked car, is an invitation to lose the stuff and to help chum the neighborhood for criminals; and
  • Given that most of the thefts are from the vehicles of park visitors, it’s past time for some LARGE signs in the 4200 block and at the Nature Center and 4100 Hillcrest and, especially, in the 42d St. parking lot, to warn the visitors:
                                             Car Breakins Here! Lock your junk in your trunk.

If you share my view on that, please contact our Councilwoman and fill in the Park Master Plan Questionnaire.  Here is what I said there:

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College Graduation Rates

The SCHEV Web site has cohort graduation rates for first-time, full-time freshmen in our four-year institutions.  Because the data include the six-year rate, the most recent report is for the cohort that entered in 2012-13.

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The numbers in the green bars are the 4-year rates; those outside the end, the 6-year.  You’re on your own for the five-year rates.

Notice JMU and University of Richkids approaching the W&M/UVa rates and notice especially W&L leading the pack.

If we calculate the ratio of the 4-year to 6-year graduation rates, we get:

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The lower average rate for the public schools reflects the relatively larger 5- and 6-year rates at the urban schools, the former teachers’ colleges, and Tech.

Comcast vs. the Neighborhood

Returning home from the gym yesterday, I found the alley blocked by a vehicle.

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Judging from the sign on the side of the vehicle, the driver is a Comcast contractor (without the required Virginia plates, it seems).

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Getting no response from a polite honk of my horn, I resorted to a more robust sounding.  That produced the driver, walking down the (empty) driveway of the house to the right and rear of this picture.

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I asked if he would move the car.  He said no.

I turned around and drove around the block to get to the other end of the alley, thinking unkind thoughts about Comcast.

This kind of behavior does not improve Comcast’s (already less than wonderful) reputation.