@everytreenyc

At the beginning of June I participated in the Trees Count Data Jam, experimenting with the results of the census of New York City street trees begun by the Parks Department in 2015. I had seen a beta version of the map tool created by the Parks Department’s data team that included images of the trees pulled from the Google Street View database. Those images reminded me of others I had seen in the @everylotnyc twitter feed.

silver maple 20160827

@everylotnyc is a Twitter bot that explores the City’s property database. It goes down the list in order by taxID number. Every half hour it compose a tweet for a property, consisting of the address, the borough and the Street View photo. It seems like it would be boring, but some people find it fascinating. Stephen Smith, in particular, has used it as the basis for some insightful commentary.

It occurred to me that @everylotnyc is actually a very powerful data visualization tool. When we think of “big data,” we usually think of maps and charts that try to encompass all the data – or an entire slice of it. The winning project from the Trees Count Data Jam was just such a project: identifying correlations between cooler streets and the presence of trees.

Social scientists, and even humanists recently, fight over quantitative and qualitative methods, but the fact is that we need them both. The ethnographer Michael Agar argues that distributional claims like “5.4 percent of trees in New York are in poor condition” are valuable, but primarily as a springboard for diving back into the data to ask more questions and answer them in an ongoing cycle. We also need to examine the world in detail before we even know which distributional questions to ask.

If our goal is to bring down the percentage of trees in Poor condition, we need to know why those trees are in Poor condition. What brought their condition down? Disease? Neglect? Pollution? Why these trees and not others?

Patterns of neglect are often due to the habits we develop of seeing and not seeing. We are used to seeing what is convenient, what is close, what is easy to observe, what is on our path. But even then, we develop filters to hide what we take to be irrelevant to our task at hand, and it can be hard to drop these filters. We can walk past a tree every day and not notice it. We fail to see the trees for the forest.

Privilege filters our experience in particular ways. A Parks Department scientist told me that the volunteer tree counts tended to be concentrated in wealthier areas of Manhattan and Brooklyn, and that many areas of the Bronx and Staten Island had to be counted by Parks staff. This reflects uneven amounts of leisure time and uneven levels of access to city resources across these neighborhoods, as well as uneven levels of walkability.

A time-honored strategy for seeing what is ordinarily filtered out is to deviate from our usual patterns, either with a new pattern or with randomness. This strategy can be traced at least as far as the sampling techniques developed by Pierre-Simon Laplace for measuring the population of Napoleon’s empire, the forerunner of modern statistical methods. Also among Laplace’s cultural heirs are the flâneurs of late nineteenth-century Paris, who studied the city by taking random walks through its crowds, as noted by Charles Baudelaire and Walter Benjamin.

In the tradition of the flâneurs, the Situationists of the mid-twentieth century highlighted the value of random walks, that they called dérives. Here is Guy Debord (1955, translated by Ken Knabb):

The sudden change of ambiance in a street within the space of a few meters; the evident division of a city into zones of distinct psychic atmospheres; the path of least resistance which is automatically followed in aimless strolls (and which has no relation to the physical contour of the ground); the appealing or repelling character of certain places — these phenomena all seem to be neglected. In any case they are never envisaged as depending on causes that can be uncovered by careful analysis and turned to account. People are quite aware that some neighborhoods are gloomy and others pleasant. But they generally simply assume that elegant streets cause a feeling of satisfaction and that poor streets are depressing, and let it go at that. In fact, the variety of possible combinations of ambiances, analogous to the blending of pure chemicals in an infinite number of mixtures, gives rise to feelings as differentiated and complex as any other form of spectacle can evoke. The slightest demystified investigation reveals that the qualitatively or quantitatively different influences of diverse urban decors cannot be determined solely on the basis of the historical period or architectural style, much less on the basis of housing conditions.

In an interview with Neil Freeman, the creator of @everylotbot, Cassim Shepard of Urban Omnibus noted the connections between the flâneurs, the dérive and Freeman’s work. Freeman acknowledged this: “How we move through space plays a huge and under-appreciated role in shaping how we process, perceive and value different spaces and places.”

Freeman did not choose randomness, but as he describes it in a tinyletter, the path of @everylotbot sounds a lot like a dérive:

@everylotnyc posts pictures in numeric order by Tax ID, which means it’s posting pictures in a snaking line that started at the southern tip of Manhattan and is moving north. Eventually it will cross into the Bronx, and in 30 years or so, it will end at the southern tip of Staten Island.

Freeman also alluded to the influence of Alfred Korzybski, who coined the phrase, “the map is not the territory”:

Streetview and the property database are both a widely used because they’re big, (putatively) free, and offer a completionist, supposedly comprehensive view of the world. They’re also both products of people working within big organizations, taking shortcuts and making compromises.

I was not following @everylotnyc at the time, but I knew people who did. I had seen some of their retweets and commentaries. The bot shows us pictures of lots that some of us have walked past hundreds of times, but seeing it in our twitter timelines makes us see it fresh again and notice new things. It is the property we know, and yet we realize how much we don’t know it.

When I thought about those Street View images in the beta site, I realized that we could do the same thing for trees for the Trees Count Data Jam. I looked, and discovered that Freeman had made his code available on Github, so I started implementing it on a server I use. I shared my idea with Timm Dapper, Laura Silver and Elber Carneiro, and we formed a team to make it work by the deadline.

It is important to make this much clear: @everytreenyc may help to remind us that no census is ever flawless or complete, but it is not meant as a critique of the enterprise of tree counts. Similarly, I do not believe that @everylotnyc was meant as an indictment of property databases. On the contrary, just as @everylotnyc depends on the imperfect completeness of the New York City property database, @everytreenyc would not be possible without the imperfect completeness of the Trees Count 2015 census.

Without even an attempt at completeness, we could have no confidence that our random dive into the street forest was anything even approaching random. We would not be able to say that following the bot would give us a representative sample of the city’s trees. In fact, because I know that the census is currently incomplete in southern and eastern Queens, when I see trees from the Bronx and Staten Island and Astoria come up in my timeline I am aware that I am missing the trees of southeastern Queens, and awaiting their addition to the census.

Despite that fact, the current status of the 2015 census is good enough for now. It is good enough to raise new questions: what about that parking lot? Is there a missing tree in the Street View image because the image is newer than the census, or older? It is good enough to continue the cycle of diving and coming up, of passing through the funnel and back up, of moving from quantitative to qualitative and back again.

On pet parents

I’m a parent. It doesn’t make me better or worse than anyone else, it’s just a category that reflects some facts about me: I conceived a new human with my wife, we are raising and caring for that human, and we expect to have a relationship with him for the rest of our lives. Some people don’t take parenthood seriously, so it doesn’t impact their lives very much, but their kids suffer. We take it very seriously, and it’s a lot of work for us.

I also take care of pets. We own three cats, and sometimes I walk my mom’s dog or take him to be groomed. It can be a lot of work, and the relationships can be very intimate at times. “Ownership” is kind of a funny word for it. In some ways it can be like certain stages of parenting: we buy all the food and make sure the animals don’t get into danger. It makes sense when I hear people refer to their pets as their “baby” or put words in their pets calling themselves “daddy.” I even understand when I hear them refer to themselves as “pet moms.”

I understand this usage, but I do not agree with it. I have a kid, and I have pets. The relationships are similar, but different. When someone calls themself a “pet dad,” it trivializes my relationship with my kid and infantilizes my pets. It erases the work of the actual parents, and trivializes the hard work of humans who act as surrogate parents to infant pets. I am a dad: I am not a pet dad, and I am not my pets’ dad. Or their mom.

My kid will one day be an adult, and while I may always think of him as The Kid, he will be able to function as an autonomous member of society. (Note that the term “kid” itself is an animal metaphor – referring to a juvenile goat.) Only one of my cats can still be considered a juvenile by any standard; the others are five years old and twenty years old, respectively. They are adult males, and until the last century they would have been free to come and go as they wished.

If my cats are incapable of leaving our house unaccompanied it is more likely due to the fact that we have cars everywhere than anything else. When I was a kid we lost three dogs to car culture. When I was eleven I saw a neighbor’s cat crushed beneath the wheels of a car, and arrived just in time to see him take his last breath. We have indoor cats and dog leashes in part because we have made the outdoors inhospitable.

I suspect one reason we hear more about “pet parents” is that so few of our pets are parents themselves. I support universal neutering, and have only adopted neutered cats from shelters or feral rescuers. It’s the best response to the overpopulation of feral animals, but it does make the pets neuter – and childless.

When I was a kid we had a cat who had a litter of kittens. I watched one of our dogs give birth to eleven puppies, and then found homes for the ten that lived. Our male cats were aggressive, sexual toms. Again, not wise in retrospect, but it was hard to think of any of the humans in the house as “moms” or “dads” of our pets while they were themselves moms and dads.

There is one human I know who would qualify as a “cat mom” in my mind. She is the woman who leads the feral cat helpers in our neighborhood. Six years ago someone found a baby kitten near some railroad tracks in Manhattan. My neighbor fostered this kitten in her apartment for five months, feeding him with an eyedropper until he was old enough to eat. She posted his picture on her website and we adopted him. If he has a “pet mom” it’s her.