Tuesday

Global Warming Measurements, now on Twitter

 
Here's another way of looking at climate change: measuring the carbon dioxide (CO2) in the air. And that's what the Mauna Loa record, which has been kept since the late 1950s, does. It's also known as the Keeling Curve, after Charles David Keeling, who set up the program and directed it for many years. 

Keeler was one of the first climate scientists to discover that the earth might behave with surprising regularity (given the right scale), and the long-term effort to measure atmospheric CO2 grew out of that insight. 
The value of the Mauna Loa record soon became readily apparent. Within just a year or two, Charles David Keeling had shown that CO2 underwent a regular seasonal cycle, reflecting the seasonal growth and decay of land plants in the northern hemisphere, as well as a regular long-term rise driven by the burning of fossil-fuels.
There's some fascinating history at the website of the Scripps Institute of Oceanography here, which was Keeling's academic home. And now Scripps is posting the daily Keeling Curve on Twitter. You can follow it here. What does it mean? Atmospheric carbon dioxide has been increasing steadily. You can see the measure is approaching 400 ppm - a threshold that will mean a different climate. You can read more here.

Friday

Hiatus week of April 22

I will be on a break from blogging next week with a last-minute large project and then some travel. In the meantime, if you haven't already seen it, make sure you read Paul Krugman's New York Times column about the "Excel depression." It's his take on the economic paper that concluded that once national debt exceeds 90 percent of gross domestic product economic growth drops off sharply. The claim gave some theoretical weight to the politicians who argued for economic austerity. Turns out the paper may have been, um, incorrect.

Yes, there was a coding error and, according to Krugman, they omitted some data and used 'questionable statistical procedures.' They've now released their data and original spreadsheet, which is how these errors came to light. You can see sections of the original spreadsheet here, if you're interested. But as is often the case, the issue was as much about how the original study was used and reported. As Krugman puts it:
[The] tipping-point claim was treated not as a disputed hypothesis but as unquestioned fact. For example, a Washington Post editorial earlier this year warned against any relaxation on the deficit front, because we are “dangerously near the 90 percent mark that economists regard as a threat to sustainable economic growth.” Notice the phrasing: “economists,” not “some economists,” let alone “some economists, vigorously disputed by other economists with equally good credentials,” which was the reality.
Read the full column. See you in a week.

Thursday

March weather, 2012 and 2013

 
March 2012 was unusually warm, and March 2013 unusually cold. The short-term explanation appears to lie in the Arctic Oscillation, as described in the NOAA video above. The cold March came at the tail end of a cold winter.

But there seems to be a longer-term possible explanation appearing as well. Remember climate and weather are two different things, and this video describes the weather. But yes, the climate is changing. And one of the effects appears to be on sudden stratospheric warming events like the one that occurred last January.
Sudden stratospheric warming events take place in about half of all Northern Hemisphere winters, and they have been occurring with increasing frequency during the past decade, possibly related to the loss of Arctic sea ice due to global warming. Arctic sea ice declined to its smallest extent on record in September 2012.
And yes, sudden stratospheric warming events can affect the Arctic Oscillation. You can read more about them here. As they say, you can expect the climate; the weather is what you get.  

Update, May 6: There's an interesting interview with meteorologist Paul Huttner here. He talks about the unusual weather events we've been seeing, like last week's late snowstorm. And how that's a weather event, but there are lots of signs of regional climate change around the world.

Tuesday

Social media and disasters


There's a fascinating story in The Guardian's data blog about how social media have allowed information to be shared in the aftermath of the explosions at the finish of the Boston marathon yesterday. Social media played an important role as local sites set up accommodation offers as well as information. Twitter was very important - and I learned about a site, Trendsmap, that provides real time mapping of Twitter feeds (in all languages, not just English). And it's interactive - click on one of those links and the Twitter feed appears in a window:
It appears that the investigators have found a circuit board used to trigger the bombs.

ESRI, which I've written about before, does something similar, though not in real time.

David Brooks is not thinking straight about big data

David Brooks is doing the public no favors in his column today in which he suggests, among other things, that analysis of big data is devoid of human interpretation, bias, or judgment. (I am looking forward to reading "Big Data" by Viktor-Mayer Schonberger and Kenneth Cukier.) Leaving aside the headline, which Brooks may not have written, the commenters take the argument apart pretty well. I would just add one more thing: Mr. Brooks gave Jim Manzi's "Uncontrolled" a pretty big push last year. Has he forgotten what he said then? Big data is big data.

You can read my review of "Uncontrolled" here. And if you haven't read it yet, you should.

Monday

Critical reading, of charts

Here's a very good look from the Harvard Business Review (free after registration) at how different presentations of data can reflect different interpretations. It's another reminder of how important critical thinking and skepticism are to data you are given. As author Jake Porway states:
The most troubling part of all this is that "we the people" rarely have the skills to see how data is being twisted into each of these visualizations. We tend to treat data as "truth," as if it is immutable and only has one perspective to present. If someone uses data in a visualization, we are inclined to believe it. This myopia is not unlike imagining the red velvet cake we see in front of us to be the only thing that could have been created from the eggs and milk we mixed together to make it. We don't see in the finished product the many transformations and manipulations of the data that were involved, along with their inherent social, political, and technological biases.

Friday

"Data can be a source of creativity and art"


Shakespeare Machine Doc from Ben Rubin on Vimeo.

Last Friday I heard Mark Hansen of the Columbia Journalism School speak at a panel presentation on uses of data - that's a quote from his presentation in the post title. (You should click on his name just to see who funded the institute he heads.)

The Shakespeare Machine has 37 long screens, one for each of Shakespeare's plays. Hansen, a statistician, worked with artist Ben Rubin to develop algorithms that identify different word combinations. There might be a display of "you ___" words - "you gold, you king, you fool" appear on blade after blade. As Artnews describes it:
Each blade contains a whole play. Once a cycle, for about two minutes, the blade streams its play in its entirety. Then selections from its text will appear–terms selected for grammatical, contextual, rhythmic, or semantic attributes, like a verb followed by the word it, a noun phrase containing a part of the human body, and adjective-conjunction-adjective.
The Shakespeare Machine has been installed in the lobby of the Public Theatre in New York. So brush up your Shakespeare - and see if you can figure out which blade matches which play.

Thursday


That's a map of state-by-state obesity trends in the US, measured by BMI (body mass index). That's a pretty rapid shift, in the 25 years from 1986 to 2010. Further data from the CDC here. I've written about obesity before, here for example, but it's always good to see the data in a larger context.

Art Networks


The Museum of Modern Art, in New York, has an extremely lucid and accessible show "Inventing Abstraction" on view. It's full of fascinating and often tessellated or otherwise mathematical works of art. You can see some of them at the exhibition's website.

The network in the screenshot at the top of the post is reproduced at the entrance to the exhibition. It illustrates the extensive connections between the early abstract artists; those the most documented connections are illustrated in red. It's fascinating to look at - you'll identify patterns of geography as well as influence if you look closely. The online version is interactive. Click on Vaslav Nijinsky's name, for example, and you'll find connections to Claude Debussy, which is not surprising, and to Duncan Grant, a connection which was new to me. As was Nijinsky's art on paper, three pieces of which are included in the exhibition.



Tuesday

Social Impact Bonds in New York and elsewhere


I last wrote about social impact bonds back in August and its sister health impact bonds about a month later. The field is moving, and it's time for an update. According to news reports like this one, there are 14 social impact bonds (SIBs) issued or in development in the UK. The UK organization Allia, "The Social Profit Society," has issued what it calls a "Future for Children" bond. And New York's own SIB has moved from pilot stage to full implementation.

New York City's efforts focus on youth held at the City's jail at Riker's Island, where a bed costs $85,000 a year. Studies show that youth who have been in custody are likely to return to jail over the succeeding six years. It's obviously better for the youth not to return to jail, and there's a large possible savings in reducing their future days in jail. In New York, the SIB-funded program provides a specialized cognitive behavioral therapy program called Moral Reconation Therapy (MRT) to 16-18 year olds who are held at the City's jail on Rikers Island for four days or more.

You'll notice, from the screenshot illustrating the transactions among the players in New York City's SIB, that there are some differences from the simpler model I described in my earlier post. Evaluation is expensive, and the independent evaluator is funded outside the SIB. So is the work of the intermediary, MDRC. The other major difference is the funding mechanism itself: Goldman Sachs has loaned MDRC, the intermediary, $9.6 million. That loan is backed by a $7.2 million grant from the Bloomberg Family Foundation. If the program succeeds - its break-even point is a 10% reduction in future jail days - the investors profit, and there are large possible savings for taxpayers. If the program does not succeed, Goldman has not put all its money at risk.

Why this structure? Not all social programs are equally successful. The least risky are evidence-based programs, those that have been shown to be successful, at least for a well-defined population over a set amount of time. Other programs, like MRT are quasi-evidence based: the research results are mixed. (One reason MRT was chosen as the intervention is that it fits well into the jail's operations.) New, untested programs are the riskiest. Even tested programs can be risky: a SIB-funded program might require a scale of services that has never been used. The challenges of translating a program that works in one setting (the community) to another setting like a jail also increase the uncertainties.

A couple of other things to note. A lot of learning happened during the pilot period. Although there's no opting out of the prison-based program, a lot of kids weren't participating, and "we had to figure out why," says MDRC's David Butler. In jail, there may be a lot of reasons that have nothing to do with the program, such as administrative and punitive segregation, or programs cancelled due to various jail issues. As in many other social service programs, data collection is a challenge. MDRC staff member Timothy Rudd pointed out other uncertainties to the program as well. Any savings are not spread out evenly over all program years, but become more evident, if they exist, in later years. And while the evaluation will examine the first cohort of participants, those results will be extrapolated to five subsequent cohorts.

So this is a program to watch. I'll keep updating every six months or so, as we see what happens.

Monday

Climate news roundup from Climate Central


That image? It's a toxic tide in Lake Erie - something that, as Climate Central reports, could come more often, with greater intensity, as the climate warms. 

It's just one of six images, linked to related reports, in Saturday's "Six to See" Slideshow on Climate Central's website. Another story covers NOAA's new hurricane warning and watch system, developed in response to Hurricane Sandy.
Beginning on June 1, the agency will be permitted to leave watches and warnings in effect even if a hurricane transitions into a post-tropical cyclone, which technically speaking is a different type of storm than a storm of purely tropical origins, provided that the storm still poses “a significant threat to life and property.
Other stories involve Antarctic sea ice, projected droughts this summer in the Western United States, and other economic and social impacts of climate change.

Thursday

A good illustration of the importance of early childhood education

If you haven't seen it already, Eduardo Porter's column in the New York Times yesterday morning, "Investments in Education May Be Misdirected" is worth reading. In it, Porter argues that the US is misdirecting its education spending by focusing so much on middle school, high school, and college students, and less on younger children. Porter reports:
Public spending on higher education is more than three times as large as spending on preschool, according to O.E.C.D. data from 2009. A study by [Julia] Isaacs found that in 2008 federal and state governments spent somewhat more than $10,000 per child in kindergarten through 12th grade. By contrast, 3- to 5-year-olds got less than $5,000 for their education and care. Children under 3 got $300.
Porter argues that this distribution of funding particularly hurts children from poor families, as they come to school unprepared to learn. Julia Isaacs' study found that:
more than half of poor 5-year-olds don't have the math, reading, or behavioral skills needed to profitably start kindergarten. If children keep arriving in school with these deficits, no amount of money or teacher evaluations may be enough to improve their lot later in life.
Porter provides a link to a presentation by James Heckman that is even more interesting. Heckman argues that the cost of making up for lack of skills is very high, and that early intervention can mean great improvements in cognitive and emotional abilities, as well as health. School reform, Heckman points out, will not solve this problem. Early intervention, on the other hand, gives the child a foundation that can be built on later.

What do you think? Please comment.

Monday

Cool pavements - a little hope for climate change?


Via Grist.org - or maybe this video just explains why New York City has painted the bike lanes in my neighborhood a pastel green. You can find Grist's take here.

How representative is Facebook?

If your friends are like mine, your Facebook feed last week turned red, as people changed their profile pictures to some version of the Human Rights Campaign's equality sticker. (For a slideshow of the variety, click here.) It seemed as if everyone had changed their profile picture. But did they?

On Friday, Facebook reported an analysis by Eytan Bakshy of the changes. There was an uptick of profile photo changes last Tuesday, March 26, "around the time when HRC began urging their Facebook followers to change their profile pictures at 1 pm EST." The uptick was pretty large, with 2.7 million (120 percent) more profile photo changers than usual. Here's Facebook's graph:
Notice that there are no scales on the Y axis, and only the bottom graph has scales on the X axis. Both graphs display time series model; in the bottom, Facebook's number crunchers have smoothed out the data, presumably by lengthening the scale. But, without scales on both axes, we can't know for sure. (Without a scale, we also can't tell where the growth begins - remember, you need to know where the beginning point - 0 - is.) So what, exactly, is this graph telling us? That there was an uptick at some time between March 25 and March 27.

Did all 2.7 million users change their profile photos to some variation of the HRC meme? We have no way of knowing that. I would guess that some did, and others changed their profile pictures to something different. Also, how many people wanted to change their profile pictures but didn't want to take the time to figure out how do it? That's relevant to the next point Facebook's data team makes: that users closest in age
to 30 years showed the greatest increase in updating. This suggests that, on average, 3.5% of 30-year-old Facebook users updated their profiles in response to the events surrounding the HRC campaign. We also found a small, but significant difference expression between genders. On average, 2.3% more self-reported female users updated their profile photo, compared to 2.1% more self-reported males.
Isn't age also self-reported on Facebook, as one of the commenters on Bakshy's post points out? And while we're about it, how many of the profile changers were people as opposed to other organizations? Maybe Facebook has this information. If so, I'd like to see it included in its post.

Oh, and one more point: Facebook has more than 163,000,000 users in the United States, according to socialbakers.com. So that 2.7 million figure is less than 2% of all Facebook users.

I found this column because of a blog post by Rebecca Rosen of TheAtlantic.com titled "Facebook: 2.7 Million People Showed Their Support for Marriage Equality by Changing Their Profile Pictures." Remember, when you're reading these things: it's important to think critically about the statistics and graphs in front of you.



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