Covering Their Assets

Let me say at the outset, before indulging in any snark or sarcasm, that I sincerely appreciate the effort that community organizers, especially Chris and Magdalena at our local CDC, Neighborhood of Affordable Housing (NOAH), and state and local government representatives, have put into thinking about climate change preparedness in my community of East Boston. Okay. What follows is a short summary of a local climate change event. The facts and the absurdity are true, only the names have been omitted because I forgot them.

On Wednesday, March 25, 2015, I attended a Climate Change Workshop at my (brand, spanking new and uber-sustainable) local library in East Boston. It was well attended - at least 100 people in attendance - but like all community meetings with local government, a little less than perfect. Attendance at community meetings is always challenging, but it's awkward when residents are underrepresented.

State, regional, and city officials (as well as outside organizations and the odd graduate student) outnumbered my neighbors 2 to 1. Worse, they had taken all of the good seats and nearly cleaned out the buffet dinner. Residents, like myself, were largely relegated to the margins and forced to scrounge for cold scraps at the break. The irony doesn't end there, of course.

The first speaker, a severe-looking woman in a red suit from Massport (Massachusetts Port Authority), began her presentation with the statement: "At Massport, we have been focused on how to protect our assets." Amazingly, no one else in the room except me found this statement funny (in the picture, I'm the medium-sized guy standing at the back of the room with a bewildered look on his face).

She sped through a series of PowerPoint slides demonstrating that the airport was indeed spending time thinking about how to protect its own assets: modeling flood potential on airport property, investigating how to flood-proof doors, and ensuring that when the next super storm hits, the military would have somewhere to land and save us all. Her overarching message: what's good for the airport, is good for your community. Stirring.

Some agencies are better than others at communicating with the public.

Steve from DOT (Department of Transportation), a serial presenter at these kinds of events, used his classic sleeper move, attempting to bore the audience into submission. Indeed, an elderly woman standing next to me said (somewhat loudly), "This is boring." In place of a PowerPoint slide, Steve actually scrolled through the pages of a PDF report (including the front matter and "this page intentionally left blank" page), providing a halting monologue about the significance of this report. At some point, someone yelled, sarcastically, "You're going too fast," which almost led to him to SLOW DOWN. To our relief, he scrolled on to a page with a map and proceeded to talk about the importance of this map, without actually explaining what it showed. As far as I can tell, the map depicted, in higher-than-average resolution, areas along the central artery highway that are prone to flooding. Again, this interpretation is based on a post hoc reconstruction. 20 minutes down, 230 to go.

The guy from the Boston Water and Sewer Commission (speaking also on behalf of MWRA (Massachusetts Water Resources Authority), who were very sorry they couldn't be here) was a welcome relief. No PowerPoint or PDF. Plain English. These guys are prepared and are thinking critically, AND they know how to talk to residents. What we learned is that the system for drainage and our drinking water is constructed with enough slope that it is not at immediate risk from sea level rise or flooding. With absolutely no hint of sarcasm, he assured us that this gravity-based infrastructure is relatively safe because gravity is still working well. Thank God.

The guy from BRA (Boston Redevelopment Authority) explained that the City now has a checklist which explicitly asks property developers along the waterfront whether they have thought about sea level rise. It's not clear how many have, but they've been asked. On an equally hopeful note, he recounted how many houses are installing solar panels on their roofs. In the event of a power outage, some houses may still have power.

Other agency representatives spoke, I think.

After the speakings, we were granted a short break before reassembling by sub-neighborhood throughout the library. I dutifully joined my people in the Eagle Hill sub-neighborhood section. Agency people were to circulate amongst the three sub-neighborhoods in 20-minute rounds. Our moderator, who was from Cambridge (for which he apologized, appropriately in my opinion), endeavored valiantly to generate dialog that he could moderate.

In the first round, it was us against the severe lady from Massport and Steve from DOT. It was clear that the agencies, and some of our moderators, were still focused primarily on protecting their assets, rather than people. My wife asked a very pointed question to the Massport lady: "Do you have a plan for protecting the job security of workers at the airport in the event of a disaster or major emergency? For low wage workers, the economic disruption can be just as disastrous. Many people in this neighborhood lost jobs when public transit shut down due to the snowstorms."

Massport lady said, "That is a good point." She then laughed and said, "You know, for me, I just got five days off during the snow storm. I went skiing." She beamed with the memory. Even our moderator from Cambridge looked disgusted.

Our moderator from Cambridge asked, "Could the airport possibly be a place that people in the neighborhood could be evacuated to in the event of an impeding hurricane or other disaster?"

Massport lady said, "Well, at some point, the neighborhood has to take responsibility for itself. If a hurricane is coming, there shouldn't be anyone here." Our soon-to-be state representative (an Eagle Hill resident) pointed out that all three assisted living homes in the neighborhood are in flood-prone areas and those people cannot be easily evacuated. His mother (head of the Eagle Hill Civic Association) observed that there are no ambulances on this side of the harbor. If the tunnel to downtown Boston is closed in the event of an extreme flood event, the only emergency vehicle is at the airport.

The elderly lady I was standing next to earlier (i.e. "This is boring"), an Eagle Hill resident, threw all caution to the wind and deliberately asked Steve from DOT a question. I do not recall what he said, or maybe I just ran out of space in my head to remember his response.

In round two, it was us against the guy from BRA and a young woman from MEMA (Massachusetts Emergency Management Agency). This time, our moderator from Cambridge came in swinging, asking residents who hadn't said anything yet to please say something. I asked, "Is there a plan for encouraging more green infrastructure? One of the challenges in East Boston is the very high level of impermeable surfaces, which exacerbates flooding." After an uncomfortably long stretch of silence, the young woman from MEMA said, and I quote, "Rest assured, we are working on that." Rest assured? Has she not read the orientation manual for all incoming bureaucrats that says, "Do not, under any circumstance, respond to a member of the public with the words 'Rest Assured' unless you have traveled back in time to 1955. And you are wearing a black suit and black sunglasses"?

In round three, it was us against the guy from the Boston Water and Sewer Commission. This time, it wasn't personal. This guy listened AND he admitted that he did not know the answers to some questions. I know. He didn't even try to make up an answer. This was profoundly reassuring. Even our moderator from Cambridge was compelled to thank him for not being obnoxious.

While I think many of my neighbors walked away somewhat more informed, a number of us were left feeling even less confident and more worried about what the future might hold with regard to climate change and sea level rise as a result of these encounters. To be clear, it's not just the water we're afraid of.

I understand that this is a necessary process, and that it is messy. Kudos again to NOAH for shepherding this messy process along and bringing agency folks to the community. This is something that must be done and there is a lot of work and education that needs to happen, and much of it needs to happen with agency folks.

How long would it take to melt all the snow from Boston’s streets and sidewalks?

Record snowfall this year – at least 100 inches since late January 2015 as of this writing – has nearly brought the City of Boston to its cold knees. The City has made a valiant (or maybe quixotic) attempt to attack the problem head on by employing diesel-powered snow melters. The Mayor has touted the tonnage of snow melted as a measure of progress. The city has use of four (borrowed) snow melters, with a combined capacity of melting 700 tons of snow per hour. That sounds impressive, but how big of a dent does it make? Let’s figure it out.

According to MassDOT data, there are approximately 1,332 miles of roads and rights of way in Boston. If we take into account the widths of these roads and rights of way (including sidewalks), we calculate a total area of 10.71 square miles or 298,643,564 square feet.

Let’s assume 100 inches of snow has fallen uniformly across Boston, which equates to a depth of about 8.33 feet of snow (taller than Big Bird!).

The volume of all this snow is then Area x Depth = 2,488,696,367 cubic feet of snow on Boston’s streets and sidewalks. Whoa.

 Because it’s been so cold, we can assume that the snow has been fairly light and fluffy (yet no less annoying). Let’s assume a density of 10 pounds per cubic foot of snow.

The combined weight of all that snow is then Density x Volume = 24,886,963,667 pounds of snow. At 2,000 pounds per ton, that comes to 12,443,482 tons of snow on Boston’s streets and sidewalks. Double whoa.

At 700 tons of snow melted per hour, the time it would take the City’s snow melters to clear Boston’s streets and sidewalks is 12,443,482 tons ÷ 700 tons/hour = 17,776 hours!

So, running around the clock – 24 hours per day, 7 days a week, 52 weeks a year - it would take just over 2 years to melt all the snow from Boston’s streets and sidewalks!

At that rate we should be ready for the next big snowstorm by late February 2017 (assuming it doesn’t snow again before then).

Of course, this whole exercise may sound a little unrealistic, since we all know that the City makes no effort to clear snow from sidewalks.

Are We All Ferguson?

How unique is the situation in Ferguson, Missouri - racially speaking?

What does the shooting of Michael Brown in Ferguson, Missouri and the ensuing debates and protests say about race relations in America?

Salem State's Center for Diversity and Multicultural Affairs recently organized a panel and discussion on the issues raised by Ferguson, which I had the privilege of being on, along with three co-panelists: Dr. Tiffany Chenault – Sociology, Dr. Forrest Rodgers – Criminal Justice, and Deputy Director Rahsaan D. Hall Esq. - Lawyers' Committee for Civil Rights and Economic Justice.

Each of the panelists was given full license to talk about any aspect of the issues raised, and I focused my 15 minutes on the issue of segregation. As a geographer, I thought it appropriate to look at how racial tensions play out spatially.

Before I get too far, let me lay out the more counter-intuitive take-home points I want to make:

• The US is an increasingly diverse nation, and it is still very segregated
• The most segregated racial group is Whites
• Race relations in America are not Black and White; they are multi-racial and multi-ethnic 
• School children are the most diverse and the most racially isolated amongst us
• Our regional stereotypes of where segregation is a problem, and where it is not, are probably wrong
• Ferguson, Missouri is no different than any other community in America, and that's the problem

Measuring Segregation

What is segregation?  At its most basic, segregation is the separation of groups of people - by race, class, religion, etc - within a country, community, or establishment. Actually identifying and measuring segregation, however, is not so simple.  In fact, researchers have been debating how to measure segregation for decades, and dozens of segregation indices have been proposed. In the late 1980s, Douglas Massey and Nancy Denton, two lions in the field of race studies, cleared the deck somewhat by performing a systematic analysis of 19 of these segregation indices. They concluded that segregation is not a singular phenomenon, but rather can be understood as consisting of 5 dimensions of spatial variation:

1. Evenness
2. Exposure
3. Clustering
4. Concentration
5. Centralization

Nearly two decades later, Sean Reardon and David O'Sullivan proposed an even simpler conceptualization of  residential segregation consisting of only 2 dimensions:

1. spatial exposure/isolation: the extent that members of one group encounter members of another group (or their own group, in the case of spatial isolation)
2. spatial evenness/clustering: the extent to which groups are similarly distributed

Reardon and O'Sullivan offered the following graphic to illustrate this two-dimensional idea of segregation.

Reardon and O'Sullivan. 2004. “Measures of Spatial Segregation.” Sociological Methodology 34(1):121-162.

The authors explain the graphic this way:

"In the upper half of the diagram are two patterns where black and white households are evenly distributed throughout space. Both of these patterns have low levels of spatial clustering (or high levels of spatial evenness). In the pattern on the upper right, however, there are more black households in the local environment of each white household (and vice versa) than in the pattern on the upper left; this means that the white-black exposure is higher on the right, and the white isolation is higher on the left. In the bottom half of the figure, both patterns show greater clustering—but roughly the same levels of exposure—than the corresponding patterns above."

Here is another way of looking at it.

Imagine a town (large box on the right) in which 3/4 of the people are blue and 1/4 are red. The town's overall population is represented by the larger people figures on the left. Now, assume that the town is made up of 4 neighborhoods, each of which is represented by the smaller, interior boxes. Imagine that each of these neighborhoods is also made up of 3/4 blue people and 1/4 red people.  The populations of the individual neighborhoods are represented by the smaller people figures. In such a scenario,we can say that the groups are evenly distributed across the town because each neighborhood has the same proportion of blue to red people as the town as a whole. Red people have a high degree of exposure to blue people, but not to other red people. In any given neighborhood, the average red person is exposed to three blue people. By contrast, the blue people have less exposure to red people - only one out of three other people - and more exposure to their own kind.

Here is an alternative scenario with the same overall town population of 3/4 blue people and 1/4 red.

In this case, three out of the four neighborhoods consist entirely of blue people, and all the red people are confined to the fourth neighborhood.  It's the same overall town population as the previous example, but the distribution of the groups amongst the neighborhoods is much different. In this scenario, we can say that there is a very uneven distribution (i.e. clustered). It is uneven because the group proportions in each neighborhood are very different from the proportions of blue and red people for the town as a whole. In addition, there is even less exposure of the two groups to one another, and a lot more exposure to their own kinds (i.e. they are isolated). This latter scenario is what I think most of us imagine when we think of segregation.

Growing Diversity, Persistent Segregation

How segregated is America, and is it becoming more or less so?

In evaluating the degree of segregation, we start by looking at the aggregate demographics of the country as a whole.

PolicyMap http://www.policymap.com/

The US is a mostly White country - approximately 63% non-Hispanic White in 2013, and conversely, 37% non-White (i.e. Hispanic, non-Hispanic Black, Asian and others).

PolicyMap http://www.policymap.com/

If there was a completely even distribution of these groups (i.e. not segregated), we would expect every state in the country to have the same proportions of White and non-White people as the country as a whole. This is clearly not the case.  If we change the scale of our analysis, looking at counties rather than states, we see a more complex pattern, but the basic unevenness of the distribution is still plainly evident.

PolicyMap http://www.policymap.com/

The country's demographic profile is always changing of course.  The US population continues to grow larger, albeit increasingly slowly. Both the White and non-White groups are growing, although that growth is also uneven, both geographically and mathematically. The greatest growth of the White population is occurring largely in the West and Southwest, largely as a result of internal migration.

PolicyMap http://www.policymap.com/

By contrast, growth of the non-White population is greatest in those areas that are currently most White - central and northern parts of the country and Northeast.

PolicyMap http://www.policymap.com/

Equally important, the non-White population is growing much faster than the White population, as a result of both greater natural increase (i.e. births outpacing deaths within the country) and immigration. These two facts - the geographic spread and greater mathematical increase of the non-White population - have led many to conclude that the US is becoming an increasingly diverse nation.

PolicyMap http://www.policymap.com/

This is correct. The US is increasingly diverse because the number of racial-ethnic groups in the population is increasing and the sizes of these groups relative to each other is evening out.  However, increasing diversity of the nation is not the same as decreasing segregation of its neighborhoods.

The US2010 Project, which sponsors research to analyze demographic trends, including segregation, has identified the following trends in its most recent reports on segregation:

• Almost all communities have grown more diverse, although there is still a wide range of diversity profiles, from predominantly white communities (a shrinking number) to minority-majority and no-majority ones (an increasing number).
• Black-White and Asian-White residential segregation have been declining consistently since 1990
• In racially diverse metro areas, Whites increasingly occupy diverse neighborhoods
• In racially diverse metro areas, about half the Black population and 40 percent of Hispanics still live in neighborhoods without a White presence
• Since 1990, the highest residential segregation has remained between Blacks and Whites
• Hispanic-White residential segregation has been on the increase since 1990, especially in the West.

Segregation At a School Near You

When we talk about segregation, we tend to talk about residential segregation. However, segregation is a pernicious problem that manifests in a variety of spaces, like schools. Segregation in schools is surprising for at least two reasons: 1) this is the part of the population where demographic change is really most evident and 2) this is a space that the country has been deliberately trying to desegregate for more than half a century!

The Civil Rights Project at UCLA. 2014. Brown at 60: Great Progress, a Long Retreat and an Uncertain Future.

While a little over 1/3 of the US population is non-White, half of school children are now non-White. The school population is the leading edge of a demographic wave that is sweeping this country.

However, the experience of the average school child belies this monumental fact.

The Civil Rights Project at UCLA. 2014. Brown at 60: Great Progress, a Long Retreat and an Uncertain Future.

The racial exposure of children of different races is still very uneven, despite the increased diversity of the population of school children as a whole.  In the graphic above, note that the average White student (first column) attends a school where 72.5% of the children are White. Black students (second column) attend schools where about 48.8% of children are Black and 27.6% are White. Latino students (fourth column) are in schools that are 57% Latino and 25.1% White.  Asians (third column) are the only racial group (albeit a very large and diverse one) that is exposed more to other groups (especially Whites) than to their own. Asians are a special case who warrant a separate discussion.

In general, we can say that school children in America (except for Asians) have relatively low exposure to other racial groups. Latino school children are the non-White group that is most isolated; least exposed to the dominant group (i.e. Whites) and most exposed to their own racial group. However, it is White school children who are least exposed to other racial groups, and thus most racially isolated. We might even go so far as to say that White school children are actually the most segregated group. But we need to be careful with how we interpret the latter statement.

As the authors of Brown at 60: Great Progress, a Long Retreat and an Uncertain Future point out, "Segregation is typically segregation by both race and poverty. Black and Latino students tend to be in schools with a substantial majority of poor children, but White and Asian students are typically in middle-class schools." This poverty is not just of the individual children, but of the school and the community and their resources and opportunities. The impacts of segregation are not equal, which is one big reason why the Civil Rights Movement has fought so hard against the idea of "separate but equal."

The crusade to desegregate American schools has resulted in major change, especially in the South. In the wake of court-rulings forcing desegregation and other desegregation policies starting in the mid 1960s, schools in the South have become much less segregated.

The Civil Rights Project at UCLA. 2014. Brown at 60: Great Progress, a Long Retreat and an Uncertain Future

However, these accomplishments are fragile. Since the late 1980s, school desegregation policies have been deliberately dismantled as a result of new court rulings, and changes in attitude by the political leadership. As a result, schools have been re-segregating. However, the current state of affairs is still significantly better than it was 50 years ago before these policies were implemented. All of this speaks to the power of policy.

What's equally interesting is how these trends play out on a regional basis. While the South has long suffered under the burden and stigma of its history of racism and segregation, it is now the model of integration, and it is the rest of the country that needs to take a look in the mirror.

The Civil Rights Project at UCLA. 2014. Brown at 60: Great Progress, a Long Retreat and an Uncertain Future

The graphic above shows the level of racial segregation for Black children in schools for different regions of the country between 1968 and 2010. Over the last 40+ years, the South has experienced the largest drop in segregation, followed by the West, and these two regions now have the lowest levels of school segregation for Black children. The Midwest and Border regions (i.e. the historic border between "free" and "slave states") have had modest decreases in segregation. The Northeast, by contrast, has only grown more segregated since the late 1960s and now represents the most racially segregated region of the country for Black school children. This may be a little upsetting to people who still harbor the myth of the liberal and tolerant Northeast (too often set in contrast to the stereotype of an irredeemably racist and intolerant South).

Ferguson, Missouri

How segregated is Ferguson, Missouri, and is it becoming more or less so?

Ferguson is a smallish suburban city (population ~21,000)  in St. Louis County, Missouri. It is part of the Greater St. Louis metropolitan area and a part of the Midwest.  While most of St. Louis County is White, Ferguson and neighboring towns are predominantly Black. According to the ACS 2008-2012, Ferguson is 67% Black and 31% White.

PolicyMap http://www.policymap.com/

Blacks were once a minority in Ferguson. In fact, in 1990, White residents made up 74% of the population, while Blacks were only 25% - the opposite of today's situation. But the city's demographics were shifting; White families were moving out to surrounding suburbs, and Black families were moving in.  By 2000, Ferguson's White population had declined by nearly 50%.  Whites were still a majority in 2000, but the trend was clear. This process by which communities change racially is sometimes described with the benign label of "neighborhood succession," although it may often be described as "White flight."  It is a an all too familiar phenomenon, one process by which the geography of segregation is created and maintained.

The most commonly used measure of segregation is the dissimilarity index. The dissimilarity index reflects the relative distributions of two groups across neighborhoods within a city or metropolitan area; a measure of evenness. It can range in value from 0, indicating complete integration, to 100, indicating complete segregation.  According to the Population Studies Center at the University of Michigan, the greater St. Louis metropolitan area had a 2010 Black-White dissimilarity score of 72.3, meaning that 72.3% of White (or Black) people would need to move to another neighborhood to make Whites and Blacks evenly distributed across all neighborhoods. 

CensusScope http://www.censusscope.org/us/m7040/chart_exposure.html

The level of segregation, as measured by this dissimilarity index, has actually dropped by about 6% since 1990. However, the St. Louis metro region is still the 7th most Black-White segregated major metropolitan region in the US.

CensusScope http://www.censusscope.org/us/m7040/chart_exposure.html

Not surprisingly, the racial exposure of different groups in the St. Louis metro region is also uneven. In the figure above, the rightmost column shows the racial composition (or diversity) of the metro area as a whole. The first five columns represent the average racial composition of the neighborhood of a person of a given race. Note that the racial diversity of the St. Louis metro region is not reflected by the racial exposure of its various groups. If racial exposure matched racial diversity, you would expect all six columns to be identical; that a member of any racial group was exposed to roughly 77% White residents and roughly 22% Black residents in her neighborhood. This is clearly not the case. Amongst non-White groups, Blacks are the most racially isolated. However, Blacks are still less racially isolated than Whites. Whites, once again, are the most racially segregated group; the group with the least exposure to other racial groups.

Are We Ferguson?

How segregated is my community - Salem, Massachusetts - and is it becoming more or less so?

Salem is a midsized suburban city (population ~42,000)  in Essex County, Massachusetts. It is part of the Greater Boston metropolitan area and a part of the Northeast.  Like most of Essex County, and the Commonwealth of Massachusetts, Salem is mostly White, although less so than the county or the state; Salem is 74% non-Hispanic White compared to 80% or more for the county and state. Within Salem, the largest non-White group is Hispanic. Hispanics make up 15% of the city's population, and Blacks about 5%.

CensusScope http://www.censusscope.org/us/m7040/chart_exposure.html

According to the Population Studies Center at the University of Michigan, the greater Boston metropolitan area had a 2010 Black-White dissimilarity score of 64, meaning that 64% of White (or Black) people would need to move to another neighborhood to make Whites and Blacks evenly distributed across all neighborhoods. This level of segregation has declined since 1990. Out of the 102 largest metro regions, the Boston metro region is the 27th most Black-White segregated metropolitan region in the US.

What about Hispanics? The Boston metro region had a 2010 Hispanic-White dissimilarity score of 59.6, meaning that 59.6% of White (or Hispanic) people would need to move to another neighborhood to make Whites and Hispanics evenly distributed across all neighborhoods.While this segregation score is less than that between Whites and Blacks, this Hispanic-White score makes the Boston metro region the 5th most Hispanic-White segregated metropolitan region in the country. Salem is not unlike the rest of the Boston metro region in this respect.

CensusScope http://www.censusscope.org/us/m7040/chart_exposure.html

As with the St. Louis metro region and Ferguson, the racial diversity of Salem is not reflected by the racial exposure of its various groups.  If racial exposure matched racial diversity in Salem, you would expect all six columns to be identical; that a member of any racial group was exposed to roughly 74% White residents and roughly 15% Hispanic residents in her neighborhood. This is clearly not the case. Amongst non-White groups in Salem, Hispanics are the most racially isolated. However, Hispanics are still less racially isolated than Whites. Whites, once again, are the most racially segregated group; the group with the least exposure to other racial groups. 

Again, we must keep in mind that the impacts of segregation, and its meaning, are not equal.

Are We All Ferguson?

The country is certainly diversifying, but segregation is a persistent and real phenomenon. It is not an accidental thing, and its impacts are not the same for each racial or ethnic group. Are we all Ferguson? In too many respects, yes.

The biggest questions that we are left with are familiar ones: why does this continue to happen and how can it be addressed for the long term harmony of society?

Overpopulation and climate change - too many Americans?

In a recent article timed to coincide with the UN Climate Summit in New York City, The Economist offered a ranking of “20 policies and courses of action according to how much they have done to reduce the atmosphere’s stock of greenhouse gases." A number of their choices were unexpected, such as the implementation of China’s one child policy.

China's 1-child policy ranks 4th in the list - allegedly preventing 1.3 billion tons of CO₂ from entering the atmosphere. This estimate is taken from a 2007 Reuters article in which "Su Wei of China’s foreign ministry said that his country’s one-child policy, by reducing the number of births between the late 1970s and the mid-2000s by 300m, had reduced carbon emissions by 1.3 billion tonnes in 2005 (because there were fewer people to consume goods which generated greenhouse gases in their production)."

If you do the math, this estimate assumes per capita emissions of 4.33 tons of CO₂ for each of those 300 million people whose births were avoided, which is a number consistent with the World Bank's estimate of China's per capita emissions in 2005. Although the The Economist article by no way says this, the implication is that the world is better off with 300 million fewer Chinese.

However, one offensive example deserves another. Had we arrested population growth in the US over the same period, 1970 - 2005, there would have been 95 million fewer Americans in the world. Using the per capita emissions of the US in 2005 - 19.7 tons per person - would have prevented 1.9 billion tons of CO₂. This is 1.5 times as much GHGs as that avoided by the Chinese!

One take-home message could be that more would have been accomplished by reducing the number of Americans than Chinese. Maybe America needs a 1-child policy - or the oppressive government that such a policy would require. The last is meant sarcastically.

As far as I can tell, no one is seriously offering population control as an explicit climate change mitigation policy. Nevertheless, I think the issue of population growth and its environmental implications is something worth highlighting. Indeed, fear about overpopulation is a perennial worry. There are legitimate concerns about population growth, but these are mostly to do with its relationship to the rights and status of women and local issues of economic development.  The assumption that population growth is a leading cause of global environmental degradation is really problematic because it misses (or deliberately hides) the radical inequalities in consumption between different populations. Some births have more environmental consequences than others.

It is frequently pointed out that China and India are the most populous countries on the planet (1.4 and 1.3 billion, respectively), but it is not often pointed out that the US is the third most populous country on the planet (319 million). But what's more important, from an environmental perspective, is the relative impact of these populations, not their sizes.

Consider the impact if America reduced its per capita emissions to levels similar to China, or better yet, India.

• In 2010, American emissions of CO₂ were 17.1 tons per capita, while in China they were 6.2 tons per capita, and in India, 1.7 tons per capita.
• Each American, on average, emitted CO₂ equivalent to 2.75 Chinese or 10 Indians.
• If America reduced its per capita emissions to levels similar to that of China (holding Indian emissions steady), there would be roughly 3.5 billion tons less of CO₂ in the world annually. If we treated this 3.5 billion tons of avoided CO₂ as "room" for other people to exist, this would be equivalent to making room for another 500 million Chinese, or another 2 billion Indians! 
• If the US reduced its per capita emissions to that of India (holding Chinese emissions steady), there would be "room" for another 790 million Chinese or 2.9 billion Indians!

This idea of "making room" for other people is not so radical as it might sound. Indeed, "making room" is implicitly what arguments about population growth are often really about, at least when invoked in the context of global environmental problems. But the question is: making room for who and for what?  For wealthy countries to continue a particular way of life with its high environmental impact? For poor countries to develop economically and reduce mass poverty? 

This question touches on a core debate that has plagued climate change negotiations since the 1990s; how to fairly allocate responsibility for climate change mitigation, especially between more developed and less developed countries. A large part of the problem is that consumption (as in per capita emissions of CO₂) is still a reliable proxy for wealth. Wealthier countries (and individuals) consume more (emit more CO₂ per capita) than less wealthy countries (and individuals). So long as this relationship between wealth/development and consumption hold, we have an environmental and a moral dilemma. This is the core challenge.

What Makes Data Meaningful?

Telling Tales

Context, of course. Especially narrative context. Putting data into the context of a story makes that data more intuitively understandable, more interesting, more accessible, maybe even more provocative. This was the theme of MAPC's annual Data Day event on June 22: "Data and Story Telling." The keynote presentation was by Boston Globe staff showcasing their 68 Blocks: Life, Death, Hope project. 68 Blocks is a multi-media showcase focusing on the Bowdoin-Geneva section of Dorchester, a Boston neighborhood that's been plagued by a murder rate that is triple that of the city as a whole. As Globe staff explained it, the point of their project was to understand why violence is so persistent in this neighborhood, to tell its stories in a way that hasn't happened before, and maybe, to contribute to awareness and understanding that can be part of the search for solutions.

The work they did was essentially ethnographic. A couple of reporters rented an apartment and lived in the neighborhood for 5 months, inserting themselves into the community and into the lives of a number of families and individuals. They also brought with them the documentary resources of the Globe, like photographers and videographers and sound engineers. And they cleverly tapped into both official sources of data as well as the modern social media cyberscape. The latter is what seems to have caught MAPC's attention for Data Day: using interactive maps to show violence and complaints and the more mundane demographic changes, using Instagram photos by neighborhood residents and allowing them to supplement these images with their own oral stories, etc. The reporters who spoke focused on the stories themselves and the experience of living and working in the neighborhood. At some point however, Ted McEnroe, the moderator (and PR guy for the The Boston Foundation, the event's sponsor), pointed out that the word "data" had hardly been used at all in the panel's discussion. How did the globe use data in the 68 Blocks project? I have to admit that I was bothered by this question. Wasn't it ALL data? Some was quantitative (e.g. statistics) and some was qualitative (e.g. stories, images). But we all knew what McEnroe meant by 'data': the numbers and statistics.

Letting (or Making) the Data Speak

One of the Globe staff responded, "We didn't want the story to sound or look like numbers. ... We used numbers as a way to find the story." They had of course delved into the (quantitative) 'data.' They flooded the City of Boston with Freedom of Information Act requests for public records: school statistics, numbers and types of resident complaints, service calls, sanitation, code enforcement, property records, etc. (This apparently caused some level of panic at City Hall, but that's another story.) They did the same with the Boston Police Department (e.g. 911 calls). Acquiring this data, cleaning it up, and figuring out how to present it was of course a monumental task. And they did manage to acquire a trove of data (which they are interested in sharing with academic institutions. Contact Chris Marstall at the Globe). It's clear enough how the reporters used this data in their stories: citing statistics to support claims, using numbers to hone in on issues or places of interest. But what was new to me was the activity of the Globe's 'Data Journalists' - techies of varying savvy whose job it was to make sense of the quantitative data and to figure out how to present it. They knew that their presentation of the data should work in support of the stories written by the journalists, but that was about the only guidance they had. Like true data jockies - unburdened by either theory or expertise - they took the abstracted data and looked for creative ways to present it. They sifted and sorted and experimented with different visualizations and platforms that would "allow the data to tell its own story." This sounded a little naive to me, or at least misleading.

Data is always the product of some human author - subjective at some level, or at least context-dependent. Data is not the same thing as the phenomenon it describes or enumerates. Data is a construct. Someone made a decision about what phenomena to record (e.g. crimes), what to pay attention to and what to ignore, how to count or code it, where to separate and where to aggregate, where to be precise and where to be general, and on and on, ad nauseum. The result - the data - is not a simple reflection of the phenomenon of interest. I think that a lot of us want to act as if data was authorless - just free floating facts needing to be collected and collated and then communicated. This fiction is convenient because it allows us to act as if we're working with manageable units of unfiltered observation, our perspective unsullied by some other author's dirty fingerprints. But they're there (the fingerprints), whether you see them or not. This is why metadata (i.e. data documentation) and topical expertise are so important when working with data. But the Globe took a deliberately naive approach toward the data. Their goal was to get past the preconceived solutions and cliches and stereotypes that typify discussions of neighborhood violence. Let's look at the neighborhood afresh, they said. And to be fair, their approach is a robust one - presenting the data and stories in as many ways, from as many angles, and from as many perspectives as they could manage. But for all the focus on story-telling, which is essentially linear, their approach was very non-linear, a challenging thing to reconcile.

The audience that attended this event (about 200 or so) was divided about equally among representatives from area non-profits, representatives of municipal governments, small businesses, and college students. One of the MAPC staff confided to me that they were a little nervous about how the Globe's presentation on its 68 Blocks project would be received. At first glance, it might appear to be another sensationalistic, voyeuristic tour of violence and grief in a poor, minority community. But it clearly wasn't perceived that way. One woman stood up to praise the Globe. She represented an anti-violence group and had recently lost her own son to violence. She wanted to thank the Globe staff for their respectful and sympathetic coverage of her tragedy and that of others. But the more common question was simply "How can we do that? How can my organization leverage these tools to tell our stories?" Never mind that year's worth of deep, ethnographic journalism, tell us about the cool web tools. Here is a listing of the tools mentioned:

Data Science Toolkit. Open-source tools to geocode data.	TimelineJS. Open-source tool that enables you to build visually-rich interactive timelines.	Data for Radicals. Illustrated guide to making a data-driven map with TileMill.
myNeighborhood Census Viewer. U.S. Census 2010 – Data for the City of Boston. Interactive map tool from the Boston Redevelopment Authority.	Google Fusion Tables. Tool for sharing, visualizing (maps and graphs), and collaborating with data.	Google Refine. Tool for working with messy data, cleaning it up, transforming it from one format into another, extending it with web services, and linking it to databases.

Cleaning Up Dirty Data

Alvin Chang, one of the Globe's lead Data Journalists, said, "People often think that data is just out there. Data is not just out there." Even if the data you want is available (a big 'if'), it is rarely in the form that you need it. It needs to be cleaned up, reshaped, reformatted to fit your purposes. This is one of the aspects of the Big Data revolution that is under appreciated.

In the case of the 68 Blocks project, Globe journalists faced a significant hurdle in compiling data about the Bowdoin-Geneva neighborhood: the neighborhood does not exist as a unit of measurement for any public agency. You cannot simply call up City Hall, or the Police Department, or the school district office, or even the U.S. Census and ask for records for the Bowdoin-Geneva neighborhood. Nobody gathers or holds information for such a place. Bowdoin-Geneva is a segment of the Dorchester neighborhood of Boston (which is itself fuzzily defined). It is spread across several ZIP codes which extend outside the neighborhood, somewhat overlapped by a little more than three Census Tracts, is served by various schools in and out of the neighborhood ... you get the idea. How do you gather information about a place that is not an official unit of measurement? This is an old geographic problem and there is no simple solution. It is a familiar challenge for geospatial analysts. Options are to (re)gather or (re)compile the data according to the area of interest, or to slice and dice the overlapping data units (i.e. lines or polygons) that are available (e.g. ZIP codes, Census Tracts), and make some serious statistical assumptions. Either way, the choices are labor-intensive and highly prone to error. But the results, if successful, are powerful. If you can tie different data sets together based upon location, whether or not they were originally collected with that purpose in mind, you have opened up the possibility to combine data sets from different sources and to examine their relationships.

The ability to clean up dirty data - to reshape and combine disparate sets of data - and to find connections and relationships not otherwise visible in the source data is a powerful ability. It can also be threatening.

Making Connections with the Data

During the afternoon plenary, Latanya Sweeney, from Harvard University's Data Privacy Lab, spoke about the privacy issues surrounding Big Data, and specifically, the increased capacity of commercial organizations to link together databases and thereby discover information about individuals that should be private. The example she used was healthcare data, and she demonstrated her example with theDataMap tool - a network visualization tool that allows you to see how an individual's healthcare data is shared between different organizations, from doctors and hospitals, to government agencies, to pharmaceutical companies and other private entities. One of the more profound implications from her research, which the tool shows, is the proliferation of entities sharing in an individual's information. But even more startling is how easily data privacy standards to protect individuals can be circumvented because of the proliferation of data sharing connections. While data privacy laws, such as HIPPA, require that individual healthcare records be "de-identified" before being shared, so that outside organizations cannot see the names or personally identifying information connected with those records (e.g. diagnoses for diseases, hospital admission history, etc.), it is quite possible for those organizations to deduce or reconstruct that individually identifying information. The method is a classic step in "data cleaning" and preparation - finding "key" variables or characteristics that can clearly link records across different databases. It turns out that birth dates are very powerful in this respect, especially when they can be combined with gender and geographic location. Statistically, it is HIGHLY unlikely that anyone living in your neighborhood has both the same gender and the same birth date as you. You can see how this works in a somewhat creepy application at aboutmyinfo.net, which was developed from Dr. Sweeney's research. If you can clean up dirty data, you might be able to see the dirty laundry. What tales we can tell then!

Creative Presentation of Data

In a completely rational society, evidence of a problem would be enough to motivate action when action was warranted. But since we don't live in that society, we must find other ways to motivate ourselves and our neighbors. Teens at the Urbano Project have taken a creative approach to data in an effort to spark discourse, and possibly, social change. Urbano is a non-profit organization that invites professional artists to work with high school youth "to effect social change through participatory works of contemporary art and performance." This spring they focused on the issue of transportation equity. Several pairs of teens focused on specific statistics of problems or inequity around the Boston region's mass transit system:

• More than one quarter of young people in Boston are unable to afford the cost of public transit, even though they are vitally dependent on that transportation.
• Over 600 forms of larceny were committed on MBTA property last year.
• The MBTA is saddled with a crushing $8.5 billion in debt which threatens its long term sustainability and service quality.
• Black commuters spend an extra 66 hours a year waiting, riding, and transferring than white bus riders in the Boston metro region.

Five teens and their artist mentors, Risa Horn and Alison Kotin, talked about the project and development of their art during a final afternoon presentation. The inspiration for the project came while the teens were visiting different Boston neighborhoods as part of their larger theme "Crossing Urban Boundaries." The youth noticed how dramatically different the transit experience was for different communities (and how much they hated getting on certain bus lines). They researched the issue of public transit in Boston, the problems faced by the system, and the inequities of experience. Armed with facts, they faced a challenge: how to express their data artistically and in a way that would inspire discourse and maybe even action.

Like most contemporary art, their work is abstract and symbolic. But it is grounded in the data. Every item and aspect of their art represents a quantum of the data. Each black bracelet is one hour a year lost in extra waiting. Each orange bucket lid is $300 million in debt burden. Every whistle is some number of crimes committed on the T. Their art was developed to be worn, allowing them to take their wobbling, clattering, clinking work onto subways and buses and other public venues. And it was meant to draw attention and questions, which it did. But they went even further, arranging a meeting with MBTA senior staff to deliver their artistic messages. Amazingly, MBTA officials (stone-faced and stuffily dressed, according to the youth) gave them 3 hours of their time for the meeting. By all accounts, this was a painfully awkward encounter. The two groups sat on opposite sides of a large conference table and proceeded to talk at, and past, one another. The funny thing is that, even from the youths' telling, it sounds like the two groups were actually in agreement about the data and the need for solutions. Same data, same basic interpretation, and lots of confusion.

There is a long and venerable tradition of artistic expression in the service of social activism. When done well, art resonates with people - much differently than arid facts or wonkish policy discourse. But was it that resonates? What message is communicated or received? What happens to the data when it becomes embedded in art? Should we even call it data when it is in this form? From my experiences with policy campaigns and social justice organizations, artistic expression and dry data discourse operate side by side ... or maybe it's along a continuum. Inside the legislative chamber, soberly dressed witnesses read aloud carefully researched statistics and analyses, or relate personal stories with a visceral effect - often heartbreaking or infuriating. Outside on the street their allies are dressed in costumes, performing an outrageous skit or stunt, highlighting the ridiculous or unjust state of affairs. In the end, if the campaign is successful, it still won't be clear what moved people to action.

Context

Clearly, "data" are more than disembodied facts. Context matters - both the way in which the data are situated and the way they are communicated. A lot of honest effort goes into trying to "reveal" the meaning of the data, although it sometimes seems that what we are actually trying to do is invest meaning into the data. I don't mean the latter to sound cynical. I believe that data are real, and that we have a responsibility to be faithful to the data. But given the incredible diversity of ways in which data can be honestly handled and understood, it seems naive - and boring - to think that there are simple truths to be extracted or that the data exist outside of our purposes.