Project Snow Job: Does Money Talk When the Snowplows Roll in NYC?

 By Jane Sasseen and Kevin R. Convey

Forty-four years ago this February, the so-called “Lindsay Snowstorm” sparked complaints that the administration of Mayor John Lindsay had left poorer areas of the city unplowed while it lavished attention on Manhattan.

Ever since, successive administrations have had to deal with the suspicion that when it comes to snow clearance in New York City – as in so many other areas – money talks.

But is it true?

As temperatures drop, winter settles in and the first big snowstorm of the season looms, we decided to take a look at the data to try to find out.

The so-called “Snowmageddon” storm of Dec. 26-27, 2010, was our test case. We thought that if any storm would reveal a socio-economic bias in the city’s snow-clearance method, it would be the sixth-worst in the city’s history, the monster that buried New York in almost two feet of snow and paralyzed much of the city for a week.

Moreover, the city’s response, like that of the Lindsay administration decades before, was an epic failure, provoking a blizzard of snarky tweets:

And a very unusual public mea culpa from the normally unapologetic Mayor Michael Bloomberg:

 First, we gathered data on snow-related problems from the city’s 311 complaint-line. If the suspicions of socio-economic bias were true, we hypothesized, there should be a higher number of complaints coming from poorer communities than from their better-heeled neighbors.

We filtered the data to include only residential street-clearing complaints beginning Dec. 26, the day the storm began, and ending two weeks later. Knowing that there were no additional storms during that period, we figured that slice would capture all complaints related to Snowmageddon. We wound up with 2,341 complaints.

(Unsurprisingly, the city employs a variety of Orwell’s newspeak in its complaint protocol. Almost none are classified as street or intersection “unplowed.” Instead, nearly all are designated as “replow” requests.)

Next we added to the map community district and neighborhood designations as well as total population, median family income and total complaints. To create an “apples-to-apples” comparison, we calculated how many complaints occurred per 100,000 residents in each of the city’s 59 community districts. Then, using the Google fusion map wizard, we overlayed the snowmageddon complaint locations.

Snowmageddon 2010: Where the Complaints Were

Uh-oh. Even a cursory glance at the map shows that our initial hypothesis doesn’t hold water.

Take Manhattan, for instance: Complaints per 100,000 residents in, say, lower-income Harlem (0) and East Harlem (1.6) were in the same range as on the toney – and residentially similar — Upper East Side (1.36).

Perhaps Manhattan, with its wide avenues, heavy traffic, and position as a transport and financial hub, is an anomaly among the boroughs when it comes to socioeconomic disparities in snow clearance.

Yet there’s no apparent correlation between wealth and number of complaints in the outer boroughs either. In Brooklyn, for example, the highest number of complaints (319 per 100,000 residents) came from the neighborhoods of Canarsie/Marine Park/Mill Basin, a high-to-middle income area. That was 10 times the rate of nearby low-income Brownsville, which recorded just 31 complaints per 100,000

A look at complaints per 100,000 residents for all city neighborhoods by ascending median family income yields little discernible pattern.


 If anything, wealthier and middle class neighborhoods seem to generate marginally more complaints, not fewer, than poorer neighborhoods. >

 So what does account for the disparity in complaints, if not wealth? Living along the southern tier of the city seems to be the determining factor.

If we draw a line on the map from the neighborhood of Rosedale in southeast Queens west and south to the northern tip of Staten Island, the highest density of complaints lies below it. These communities also happen to be among the furthest from Manhattan, home of the mayor, seat of city government, capital of the world.

So, is this yet another example of the New York City’s (and Bloomberg’s) Manhattan-centric nature? Is the distance from Manhattan the determinant for speedy and efficient snow clearing? Is it less “money talks” than “out of sight, out of mind”?

Marty Markowitz, the president of the borough of Brooklyn, which generated the second-greatest number of complaints per 100,000 residents (42) and more than half the total complaints, says yes.

“The main priority always seems that Manhattan gets the fastest and most complete snow removal,” Markowitz says, “and the further from the mother ship, the less the priority to remove snow.

“It may be due to the fact that just about every mayor in recent history is a resident of Manhattan,” Markowitz said, “and has not (directed) Sanitation to pay equal attention to how large snowfalls impact residents and businesses in both Brooklyn and Staten Island and of course Queens.”

But James P. Molinaro, borough president of Staten Island – which logged the largest number of number of complaints per 100,000 residents (68) – disagrees.

“I don’t think it’s Manhattan against the outer boroughs,” he said. “One big thing you have to remember is that the further out you get, the thinner the public transportation gets, until you get out to Staten Island, where you don’t have any at all.

“If all you have to do is walk a few blocks to the subway to get to work, you’re not going to complain,” Molinaro said. “But if you’re on Staten Island, where five percent of New York’s population owns 18 percent of the city’s cars, you can’t to work unless you’re plowed out.’’

Molinaro’s explanation is persuasive enough for his borough, but it doesn’t explain why a remote neighborhood such as, say, Bayside, Queens — where subway stops are non-existent and residents tend to be car owners — generated so many fewer complaints per 100,000 residents (23). Or why southern-tier towns such as Brooklyn’s Flatbush or Sheepshead Bay, where subway lines are copious, generated a like number of complaints

Other non-geographical explanations fail just readily. Lack of equipment? Nearly every community district in the city has a sanitation barn with snow-clearing equipment assigned to it. Twisting, narrow streets? The streets of Park Slope (16 complaints per 100,000) are no more difficult to navigate than those of East New York (98). Variation in snowfall? The difference between the accumulation in Central Park and in the southern tier overall wasn’t more than a couple of inches.

For its part, the city’s investigation blamed its own failure to declare a snow emergency, a failure to salt roads in the early hours of the storm, the breakdown of traction chains on many plows and their subsequent immobilization, recent sanitation-worker layoffs and the difficulty some workers had in reaching their job sites.

But these are issues that affected the entire city more or less evenly. Though we cannot know what the motivation is, our map ratifies Markowitz’ observation. When it comes to snow clearance in New York City, geography – in the form of distance from Manhattan – appears to be destiny.

This year’s first big snow storm may prove that once and for all.

One thought on “Project Snow Job: Does Money Talk When the Snowplows Roll in NYC?

  1. Jane, Kevin,
    Excellent reporting, data analysis, data visualization, and packaging of the components. The data viz themselves are effective, clean, and visually appealing. The map successfully shows the peculiar geographic pattern of complaints, and your chart debunks the easy response that the rich gets the services.
    You’ve thoroughly examined the issue, and unlike most teams, you’ve followed up with human sources to inform the data. Smart use of other media (images, twitter screengrabs, video) to add richness to this data-driven story. I do like the conversational tone of the text, which is unusual for data stories. However, I think it takes too long to actually get to the data. I would suggest leaving the methodology discussion until after we see the data. Set up the story–see the data–then discuss consequences/analysis/methodology. Methodology need only be a sidebar, link, or footnote to these stories. In terms of design, the visual flow of the post, as I’ve mentioned before, can get tedious, so you should consider breaking it up with bold subheads/sections, using pullquotes, or boxing off graphics like your Twitter screengrabs.

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