Pearson’s Law, FAT Law (?), More Data Please

Thanks to everyone who responded publicly and privately to last week’s posts on charter data.

It really helped me clarify my thinking.

Some further thoughts below.

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Scott Pearson made an interesting point about charter growth / closures trends. Scott noted that:

  1. National new school openings have been fairly consistent over past decade: 400-500 per year.
  2. National closure rates have also been fairly consistent at 3-4%.

Given this, we get Pearson’s Law: if national new school openings and national closure rates both remain at historical constants, eventually we will hit a year of zero net new schools.

In short, because the closure rate is based on total existing charters, eventually total existing charters will be large enough that a 3-4% closure rate means more schools are closing than opening.

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Smart people at Arnold Foundation said they’d much rather know total of net new high-quality openings than simply net new openings. I agree. See end of post for all I’d want to better understand.

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Others raised the point that perhaps many of us may have been wrong: growing the sector through very high bar authorization (NY, MA, etc.) might end up being an inferior strategy scaling the sector rapidly and then cleaning it up (FAT states: FL, AZ, TX).

For whatever it’s worth, in New Orleans I think we took a middle ground here: we grew the sector with less quality control than MA but more than the FAT states.

All told, the most recent data has moved a few notches over to the FAT strategy.

But I don’t think the FAT strategy should be a law yet. Still much to learn.

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Moving forward, I think we’d be much better off we had the following national data:

  1. Total new openings
    • With new school being defined as the initiation of an expansion that will lead to an increase of enrollment of +300 students over time.
    • With data scrubbed by every state charter association contacting each operator to get exact data.
    • Maturity: school tagged as start-up, early stage replication (2-4), large CMO.
    • Quality: each operator is tagged by some quality measure (CREDO?) so we understand what % of expansions are high-quality replications.
    • Source: each school is tagged to a source, if any (Charter School Growth Fund, New Schools Venture, BES, local harbormaster, etc) so where we understand where schools are coming from.
    • Geography: Urban, suburban, rural.
    • Diversity: whether CMO leader / school leader is person of color.
  2. Closures
    • Cycle: whether closure occurred during renewal or through crisis.
    • Age: how many years charter had been in existence.
    • Enrollment: how many students school enrolled.
    • Authorizer: whether it was district, non-profit, state, or university.
    • Quality: how school performed on state tests and / or CREDO (and perhaps attainment as well).

 

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