The New York Times struggles with data: We have a very weak national discourse. As a people, we just don’t seem to be very smart.
Two apparent examples emerged in yesterday’s New York Times. Among several others!
First, a very important topic—the length of time various people had to wait in line before voting in November’s election. As everyone has heard, some people had to wait as long as eight hours before they were able to vote.
Obviously, that’s insane—an insult to our democracy.
According to this front-page report in yesterday’s Times, an analysis by the Orlando Sentinel “concluded that more than 200,000 voters in Florida ‘gave up in frustration’ without voting” because of the very long lines. That is a very serious matter, especially if we assume that the long lines may have been deliberately engineered to suppress the minority vote, as people have been alleging.
But to what extent did that actually happen? In our view, Jeremy Peters’ front-page report is monumentally worthless, despite its wealth of data.
The report is built around a large graphic. But this is pretty much what the graphic shows:
PETERS (2/5/13): The average wait nationwide was 14 minutes last year, according to Mr. Stewart’s data. Blacks and Hispanics waited an average of 20.2 minutes, compared with 12.7 minutes for whites. In the most populous areas—those with more than 500,000 voters in a county—the average wait was 18 minutes, more than double what it was in counties with fewer than 50,000 voters.Obviously, it would be better if everyone had to wait the same amount of time—blacks and whites, urban and rural. But the major problem which has been discussed does not involve the difference between waiting 20 minutes to vote, as opposed to 13.
The larger concern involves those people who were forced to wait for hours. But where did that happen? And what is the evidence that the long waiting time was deliberate? This report almost completely skips those seminal questions. It substitutes a bunch of data which are largely beside the point—and it even includes this minor point of confusion:
PETERS: Several recent polls and studies suggest that long waiting times in some places depressed turnout in 2012 and that lines were longest in cities, where Democrats outnumber Republicans. In a New York Times/CBS News poll taken shortly after Election Day, 18 percent of Democrats said they waited at least a half-hour to vote, compared with 11 percent of independents and 9 percent of Republicans.It isn’t just that Democrats outnumber Republicans in cities; Democratic politicians are usually in charge of our larger cities. If cities had the longest waits, that hardly addresses the free-floating question:
Did Republicans deliberately engineer long lines in heavily Democratic districts?
The question we should be exploring involves deliberate attempts to create eight-hour lines to suppress one particular party’s vote. In this front-page news report, Peters seems to discuss everything but that seminal question.
We thought Peters’ data were largely useless, though they gave the impression that deep analysis had occurred. That said, we were puzzled by the data in a second report, this time from the front page of yesterday’s Science Times section.
Hannah Fairfield starts her report with a reference to Lawrence Summers’ “notorious comments about women’s aptitude” in math. She then presents a short report which, truth to tell, has little to do with what Summers said—a report which is accompanied by a puzzling graphic.
In this passage, Fairfield describes the puzzle she’s attempting to solve. If we’re reading her graphic correctly, we think she has left something out:
FAIRFIELD (2/5/13): [R]esearchers have been searching for ways to explain why there are so many more men than women in the top ranks of science.As she continues, Fairfield puzzles over the detailed data which you can peruse in her graphic. Here’s what she doesn’t seem to see:
Now comes an intriguing clue, in the form of a test given in 65 developed countries by the Organization for Economic Cooperation and Development. It finds that among a representative sample of 15-year-olds around the world, girls generally outperform boys in science—but not in the United States.
What explains the gap? Andreas Schleicher, who oversees the tests for the O.E.C.D., says different countries offer different incentives for learning science and math...
In almost all of the countries shown, the gap between the boys’ and girls’ average scores seems to be very small. In the United States, boys seem to have outscored girls by less than three percent on the science test in question.
Despite Fairfield’s misleading presentation, boys outscore girls in quite a few other countries, also by margins which seem to be very small. In major countries where girls outscore boys, the differences also seem to be very small—two percent or less.
How much do such small differences matter? How much does it really matter if boys in one country are two percent better on one discrete science test, while girls in some other country display the same slight advantage?
In our view, Fairfield creates a lot of confusion through her misleading text and her "small differences" graphic. But she doesn’t seem to see the problem raised by those tiny gaps.
Is Fairfield exploring a non-problem problem? We’re going to take a guess here:
The gaps between boys and girls in some of those countries may be larger than Fairfield’s graphic makes them seem. It may have been a bad idea to present these gaps in the form of percentages—percentages which are derived from average “scale scores” on this science test.
That said, we don’t really know. Fairfield’s report strikes us as woefully weak—but then again, this is the Times.