New Neighborhood Data Offers Clues without Conclusions

A map used by the Seattle Housing Authority identifies neighborhoods, shaded in purple, where housing officials and researchers believe that poor children have particularly good odds of rising out of poverty.  Credit:  Seattle Housing Authority

Seattle    Flying into Seattle I had in my hands an article about neighborhoods in Seattle and how they influenced, and perhaps determined, the future of children raised in those neighborhoods.  The article was based on Census data tracked assiduously by Bureau statisticians and researchers from Brown and Harvard Universities.  When we think about predictive data, Seattle’s Amazon is also hard to avoid since the sites attempt to anticipate what you might possible buy from what you have bought in the past in an exercise that also seems fated.   Certainly, we could all agreed that this was just coincidence.

The same might be said of this huge data reveal.

The data seems invaluable.  Following children for years, particularly those born between 1978 and 1983 and tracking them from the census tracks they inhabited then to where they are now, including in one April Fools Day snapshot of time, the data crunchers were able to map with precision the neighborhoods where lower income children had the prospects of bettering their parents with higher income and possibly escaping poverty.

The article in the New York Times wasn’t really about Seattle of course or Charlotte, North Carolina, the other city that they highlighted.  This was also coincidence, though unlikely random.  Housing authority officials were quoted in both cities.  Using the data there seemed to be a plan to issue Section 8 vouchers that would attempt to place families with children in these seemingly better neighborhoods.  The value of the rent vouchers would have to be topped off though, because many of these neighborhoods with better schools and services were more expensive or post-gentrification, we might say.  The article didn’t mention that this HUD pilot of increasing voucher value to market rate in order not to ghettoize the placement of families is one of the programs that Trump’s HUD Secretary Ben Carson has tried to suspend and terminate.

Despite mentioning that in some census tracks federal and other programs have spent literally half-a-billion dollars, ostensibly to improve their prospects in bettering the conditions of lower income families, there’s no data that verifies that figure, other than saying community block grants and major housing developments had underpinned the expenditures.  I couldn’t read that without wondering whether those monies had been usurped for market rate, mixed-income developments or other wild developer re-purposing of CDBG monies from their intended use for lower income families to building castles in the sky for politicians and their donors.  The examples of both are legion!

The mystery that was at the heart of the data is still unsolved.  Why would the outcomes for moving forward be so different only a block away in the same school districts and with similar demographic characteristics?  Additionally, given the waiting list for housing vouchers in cities throughout the country, clearly there is no anti-poverty plan that would move everyone into these neighborhoods that have managed to stand up taller, so what does the data say about how to make existing neighborhoods better?  I don’t even want to mention that as more lower income families would be moved in, what would keep the higher income families from moving out?

There’s something going on here.  The data will surely help set a baseline, but until we know more and then do more in these neighborhoods to create change, we’re left with lots of clues, but no sure conclusions.

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