FOR decades, policy makers have treated poverty as a sign of helplessness and ineptitude. The worse off the neighborhood — the higher the rate of poverty, crime, and juvenile delinquency — the less influence it would have over its future. Social service agencies conducted “needs assessments” rather than asking residents what would strengthen their community. Government agencies or private entrepreneurs then delivered brick-and-mortar solutions — a new school, medical clinic or housing.
It seldom worked. Take Baltimore, which has been “renewed” again and again. Two decades ago, more than $130 million was poured into the neighborhood where the arrest of Freddie Gray sparked riots last spring. The vision was grand — more than a thousand homes were built or renovated; education and health services were introduced — but the jobs disappeared and the drug trade continued to flourish.
David L. Kirp
Education and inequality.
The May 5, 1958 edition of Arthur Radebaugh’s Sunday comic, Closer Than We Think, showed off the high-tech school of tomorrow. With hordes of baby boomers flooding into public schools in the 1950s, it makes sense that this strip would focus on different solutions for overcrowding with that technological optimism we identify as being uniquely post-war American.
The student desk of the future includes a small camera, presumably so that the teacher being projected on a large screen in the front of the class can keep tabs on the little rascals. One thing that fascinates me about computer consoles of the retrofuture is that the QWERTY keyboard is not yet an assumed input device.
… if you’re not careful, modelling has a nasty way of enshrining prejudice with a veneer of “science” and “math.”Cathy has consistently made another point that’s a corollary of her argument about enshrining prejudice. At O’Reilly, we talk a lot about open data. But it’s not just the data that has to be open: it’s also the models. (There are too many must-read articles on Cathy’s blog to link to; you’ll have to find the rest on your own.)
You can have all the crime data you want, all the real estate data you want, all the student performance data you want, all the medical data you want, but if you don’t know what models are being used to generate results, you don’t have much.