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Basing on 10,000 graduates of Wisconsin high schools in 1957 happens to “control for” (in a by-and-large way) many or most of the confounding influences one wou

Basing on 10,000 graduates of Wisconsin high schools in 1957 happens to “control for” (in a by-and-large way) many or most of the confounding influences one would have in a study today or in an area such as, for instance, Maryland or New York City. To your point about high school grads, though, it is absolutely worth noting that in 1957, “no child left behind” wasn’t a thing. In 1950, 36% of whites and 13% of blacks over age 25 had a high school diploma. In 2010, it was 92% and 84%. Then, graduation was generally a vocational choice by household and student rather than a performance bar. Today, it’s an externalized requirement, largely for the system to be funded: you will be graduated despite yourself. A few other diffs: 1954: Brown vs. Board of Education desegregation ordered 1951 spending per student: $215 for 155 days of school. 2010: $10,615 for 180 days of school. Average teacher salary then and now: $4K vs. $39K. 1955’s most popular youth book: Charlotte’s Web. 2012: Hunger Games.

YeGoblynQueenne 6y ago
>> Basing on 10,000 graduates of Wisconsin high schools in 1957 happens to “control for” (in a by-and-large way) many or most of the confounding influences one would have in a study today or in an area such as, for instance, Maryland or New York City. I don't understand how selecting a non-representative sub-population controls for anything! Same goes if the data was from Maryland or New York City. In any case, disentangling confounding factors and isolating the influence of IQ should be the goal of any research (though of course I can't ask that of an "analysis" published on a blog). If a dataset seems to reveal some deep relation between IQ and other outcomes because that dataset is free of confounding factors, that doesn't tell us what happens in the general case, where the confounding factors apply. In other words, there's a danger of finding what one is looking for because one is looking for it where it exists, when the goal of looking is to make sure it exists everywhere.

YeGoblynQueenne 6y ago

>> Basing on 10,000 graduates of Wisconsin high schools in 1957 happens to “control for” (in a by-and-large way) many or most of the confounding influences one would have in a study today or in an area such as, for instance, Maryland or New York City. I don't understand how selecting a non-representative sub-population controls for anything! Same goes if the data was from Maryland or New York City. In any case, disentangling confounding factors and isolating the influence of IQ should be the goal of any research (though of course I can't ask that of an "analysis" published on a blog). If a dataset seems to reveal some deep relation between IQ and other outcomes because that dataset is free of confounding factors, that doesn't tell us what happens in the general case, where the confounding factors apply. In other words, there's a danger of finding what one is looking for because one is looking for it where it exists, when the goal of looking is to make sure it exists everywhere.