grain edit is a graphic design blog that will expand your mind’s collection of graphic design to remember. It is not restricted to information graphics – in fact, most of the work has nothing to do with information graphics – but it includes a wide variety of graphic design and illustration. I’m posting this reading suggestion on a Sunday because it is a bit off the core topic here which is supposed to be social science data presented via information graphics. Still, if you are at least mildly interested in graphic design, surely you will find something you like over at grain edit. Not only can you see what ‘the work’ looks like, you can also read interviews, and get photographic studio tours with some of the designers they feature. And if you are super keen on the whole concept, their blog roll will take you on a fantastic cyber-tour of thought provoking eye candy.
I have been thinking about other ways to work with maps lately, and I stumbled upon this interactive consumption map created by the folks at the New York Times using numbers from Euromonitor International, 2007. This graph was certainly a product of a moment in time – I don’t see too many people making consumption graphs like this one these days. They might be making line graphs where the total amount of consumer spending or consumer confidence is of immense concern to finance people who are eager for the next growth period in the economy. (I’m not saying that only finance people are looking forward to economic growth, just suggesting that they are the people who spend a lot of time studying consumer behavior as they anticipate the growth period. The rest of us might be looking at our own retirement statements or home values or paychecks.)
This map approach to spending is great because the graphic designers – Hannah Fairfield, Elaine He and Kevin Quealy – realized that maps are just schematics. It isn’t necessary to stick with a country’s shape, but it is nice to keep them in about the same positions relative to one another. Freeing each country from the shape of its political boundaries allows each square country to change dimensions in direct relation to total consumer spending within a sector. The color tells us what this works out to in terms of per capita spending. If you clicked through to look at the actual interactive graphics you’ll find that if you mouse-over a country, you can see the dollar amount of the total spending for whatever sector you happen to be viewing.
The strength of this graphic is that it strips away unnecessary detail to focus your eye’s attention on the most salient information in an easy-to-digest kind of way. This is a huge improvement over the sort of thing that I see all too often (and have included a little global poverty example here). My eye is terrible at assessing relative areas when the shapes are so irregular like this. Much better to just keep the relative positions of the countries and give them square shapes that can be quickly, effortlessly scanned for the sake of comparison.
What needs work
I would have put the per capita spending in the roll-over as well. Right now it’s just the country’s total spending. I also would have thought about a way to represent all the countries that don’t even make this map. Something understated and subtle – a sprinkling of grey dots? But then those countries might look like dust…still thinking about that.
The other thing I might have liked would be to have either gone completely grey scale (preferred) or to have selected a single color for each sector with increasing saturation as spending increases. The second approach would have made more sense if the product was a series of print graphics, but the approach they actually took and the grayscale approach are better for this sort of interactive graphic in which the viewer sees only one at a time.
This graphic is a bit too cartoon-ish for my tastes but it does a good job of illustrating a health care gap that, even during the health care debate, went over-looked. I figured Halloween – a holiday whose commercialization revolves around candy – might be a good time to post the dental health care graphics developed over at the GOOD magazine transparency blog.
In the spirit of full disclosure: I was a dental assistant for a summer. The numbers here are accurate and have very real consequences. I used to see kids who did not know (they had no idea) that drinking soda was bad for their teeth. These kids sometimes had 7 and 8 cavities discovered in one check up. For older people, dry mouth would lead them to suck on lozenges or hard candy all day and they’d end up with a bunch of cavities, too. Bathing the mouth in sugar is bad. Combining the sugar with the etching acid in soda is even worse.
Once a tooth has a cavity, it needs to be filled or the bacteria causing the decay will continue to eat away at the tooth, eventually hitting the pulp in the middle of the tooth. Once that happens, the person is usually in pain and needs a root canal. Even if they aren’t in pain, they need to have the infected tissue removed (that’s what a root canal treatment does) or the infection can spread, sometimes into the jaw bone. There is no way for the body to fight an infection in a tooth because the blood supply is just too little to use the standard immune responses.
Dental decay progresses slowly. Kids lose their primary teeth any decay in those teeth goes with them. Therefore, it’s not all that common to see teenagers needing root canals. But it does happen. Root canals are expensive. It’s a lengthy procedure requiring multiple visits and a crown. Pricey stuff. BUT, this process allows the tooth to be saved. Without dental insurance, sometimes folks opt for the cheaper extraction option. Once a tooth is extracted, that’s it. It’s gone. (Yes, there is an option to have a dental implant but that’s even more expensive.) So a teenager who likes to suck on soda all day long and who may not be all that convinced about the benefits of flossing could end up losing teeth at a young age. I can tell you because I’ve seen it: a mouth without teeth is not a happy mouth. All those teeth tend to hold each other in place. Once some of them are extracted, the others can start to migrate. Extract some more and things get more interesting and people start to build diets around soft foods. Eventually, once enough of them are extracted the entire shape of the mouth flattens out – not even a denture can hang on to help the person eat.
Unfortunately, poor dental health disproportionately impacts poor people, as these graphics demonstrate. But that disproportionate impact can double down. Dental health is often seen as a sign of class status. People with poor dental health have trouble getting good jobs, especially in a service economy. For what it’s worth, I bet they also have more trouble in the dating/marriage market.
This post has nothing to do with sociology. It offers proof that I should probably learn to leave things alone sometimes.
I have long had this hunch that recipes would be better depicted not as lists of ingredients stacked upon lists of instructions but as something more well-integrated. I have many times forgotten an ingredient or messed up an instruction, and I like to think that better graphic design might be able to get me out of this problem. Professional cooks already tend to know which ingredients require what kind of process within certain recipes. For instance, when making cookies, the first step almost always involves creaming the sugars and fats together. But if you didn’t know this and you were used to making cakes (in which the wet and dry ingredients are kept separate from one another), you might absentmindedly tally up all the dry ingredients with your fats when making cookies. That would be a mistake.
So I found the recipe diagram above which is based on the Nassi-Shneiderman structured flowchart and thought it was worthy of consideration.
I wasn’t thrilled with it. In particular, I couldn’t figure out why there were so many separate ‘mix’ steps when some of those ingredients could clearly be mixed in all at the same time. I also wasn’t all that keen with the way the heating instructions were handled. I was also perplexed at the way in which the graham cracker crust was just thrown out there as an ingredient – most people make this from scratch (but I don’t have the ratios for that on hand so I didn’t try to rough them in lest someone actually use this as real recipe).
Here is my modification of the diagram, in grayscale even though I know it would look snazzy in color.
I still have difficulties with this diagram – where are the instructions? “Mix” is too broad a term. The other problem is that I still need to incorporate mention of tools into the diagram. This is related to the lack of instructions generally – if it said ‘hand mixer’ and ‘medium speed mix’ that would be clear enough for me. There has to be a good way to list ‘spring form pan’ in the graham cracker crust box, too. I could have just tools into the text, but that seemed to be cheating on the graphic sensibilities of the diagram. If there is a reason to be listing tools, one should have a place to put them outside the mention of instructions. That’s my biggest problem with recipes – all of the tools, times, temperatures, techniques, and ingredients are mashed together.
What needs work
I am not convinced that further modifications to the Nassi-Shneiderman flowchart are going to solve my problems. There has to be a better way to depict recipes that can provide the overview at a glance – including tools – but that doesn’t sacrifice all of the necessary details.
Before you read any further, ask yourself which one of these graphs is most useful. Which one has the most information? If you had to get rid of one of them but still be able to explain the basic flows of people into the US over the last century, which one would you keep? And would your story be much weaker, somewhat weaker, pretty much the same after the loss of one of the graphs?
First, I was moaning the other day about a graphic – like the one I posted recently about prescriptions for treating mental illness in the US – in which color is used to make it look like there is important information being encoded when, in fact, the colors are just pretty, nothing more. I am happy to report that in this case, the colors are not only useful, but necessary. Try to imagine looking at this thing in gray scale. It would be nearly impossible to read. So kudos for color in general. In specific, I probably would have tried to group the countries that are near each other in the world within a color family. Sweden and Norway are good examples of what I would have done throughout – they are both green, just different shades. That makes good logical sense. On the other hand, Ireland and the UK are not in the same color family and it confuses me. I also don’t see great geographic or other similarities between Canada/Mexico and China. So I would have kept the Canada and Mexico as they are and found a different color for China.
Now I’m going to get back to the question I asked at the beginning of the post: could you do without one of these graphics if you had to axe one? It’s a leading question and the answer is clearly: yes. The first one is far better than the second one. Looking at absolute flows by country of origin gives a much more interesting and fully articulated picture than looking at the relative values of people coming at any one point in time.
What Needs Work
The numbers behind this graph were pulled from Census Data, a good place to go because they are the most reliable numbers we are likely to find (at least with respect to legal immigration – undocumented immigration is, well, undocumented so the Census doesn’t help). However, the thing about Census Data is that it’s going to show us flows for a decade at a time and I wonder if it might be a little misleading to show these numbers as an augmented line graph. A bar graph might be better and here’s why: smoothing the lines implies decade reliant time trends that don’t exist. Unfortunately, in the real world, important decisions do not always take place in the same year the census is taken. The Immigration Reform Act of 1965 was right between decades. Now I know you’re thinking something along the lines, ‘anyone who studies immigration is going to know when that reform act was and when WWI, WWII, the Depression, and all sorts of other important historical events took place. we’re not idiots.’. I agree; you are not idiots.
On the other hand, if I were to create this as a bar graph, I would have the freedom to actually locate the legislation as a graphic element – a line flying a flag announcing the name of the act, for instance – right between the bars for 1960 and 1970. But of course, that would make it difficult to see how the flows are changing over time, so I might superimpose a kind of shadow version of the current line graph over (or under) the bars so that the eye can be aided in its path from one bar to the next. Line graphs do show change much better. But I like the idea of being explicit with the time periods in which the measurements occur and with the notion of leaving graphical space to add important contextual details.
This graphic was created by Thomas Brown using IBM’s free Many Eyes visualization tool. I wholeheartedly support IBM and the other companies and organizations that are making powerful visualization tools available for free. In case you aren’t familiar with them, they allow users to input data and then they take that data and produce visual representations of it. In this case, the full version of the graph is interactive – hovering the mouse will reveal greater detail about any given flow at a point in time. This is a great thing. I support layering of information. The layering available at Many Eyes does not quite make up for the inability to layer in the way that I described above, but I’m not disappointed with IBM. There are already tools for manipulating graphics. The best way to use IBM’s tool is not to expect it to do everything, but to take their visualizations and then further enhance them in photoshop or your favorite image editing software.
This graphic is about spaces but it is not a map. For whatever reason, people use maps whenever there is mention of geography, and even sometimes when there isn’t, even though the map is often not adding to the story and making it harder to immediately grok what the important patterns are. Just because geography or mobility might be part of the story you are trying to tell, it isn’t necessary to use a map to encode your narrative visually.
Um, so, I’m trying to think of what is working here. I guess we see that there are about 10 psychiatric drugs, that lots of people appear to be receiving treatment for anxiety (heck, two wars, an economic crisis, trapped Chilean miners, BP’s oil spill…all this anxiety makes sense to me). We are meant to believe that this represents a huge and possibly stifling example of big pharma. But really, this graphic doesn’t say that to me. It says “lots of people are anxious and choosing to take prescription drugs to cope”.
What needs work
Just for some crazy antic fun, infographic style, I whipped out my digital crop tool and got rid of the map just to see what we would lose. Clearly, we lose some fun. Almost all the pretty colors are gone. But the information? It’s all still there. The map was being used as a giant and rather useless crutch in this case. This is a particularly egregious case, but there are many instances of maps that don’t encode any information that is useful for the debate of the topic at hand. Ask yourself: what did the map do? Was there any variation contained in the map? Was the dataset in question geographically oriented in any way? No. No, it was not.
Thanks to Austin Haney, Sociology grad student at Kent State for sending this our way.
I have been posting about marriage lately and I thought I would take a break from that, but stick with the relationship topic. If you haven’t discovered the blog at OKCupid, I highly recommend heading over. With a strong mathematical background, the folks at OKCupid are thrilled to take their users’ likes, dislikes, and reported behaviors, run the stats, and provide us with the infographics. I promise it will be worth your while to head over…later on in the post where I located the pie charts above, there is a quote which I am reposting here because I thought it was the most hilarious reference to Karl Marx that I’ve encountered in a very long time:
According to Verta Taylor and Leila Rupp, who wrote a piece for Contexts called “Straight Girls Kissing”, homosexual experimentation in the US is possible for women in a way that it is not for men. At first glance, much of the ‘straight girls kissing’ going on at bars and fraternity parties appears to be a rather perverse appropriation of female sexuality for the visual pleasure of men. The history of the male gaze is so entrenched here that anything sexual going on with women is assumed to be for men, even when the sexual behavior is homosexual – especially if it is done in public as spectacle. [Note: If the girls kissing get so into it that they appear to be ignoring the male attention altogether, they do risk social sanctioning laced with homophobic slurs. So straight girls kissing better make sure they maintain some kind of connection to heteronormative behavior or they could, I don’t know, have beer poured all over them. See Rupp and Taylor.] What this means is that women who have experience with other women do not necessarily fall outside of the category ‘heterosexual’ which for many women, makes the experimentation seem quite a bit safer than if they felt that any homoerotic behavior would automatically queer their social sexuality. The same is not true for men.
Rupp and Taylor found that ‘straight girls kissing’ is not just another example of girls gone wild trying to get male’s attention by flaunting ‘extreme’ sexuality. In interviews, many of the women involved reported that at least some of the instances of their public encounters with other women opened up the possibility for them to explore their self-generated (rather than crowd-generate) attractions to other women. OKCupid’s report indicates that having this culturally condoned space to get out there and try kissing girls without risking the stigma of being labeled lesbian allows a fair number of women to have enjoyable encounters with other women. What’s more, a fair proportion of the women who haven’t done it feel like they are missing out.
If our heteronormative culture could relax the rigid classification of male sexuality to afford the same kind of bi-curious space for men, maybe they would feel more free to experiment with other men and enjoy themselves.
What needs work
I hate pie charts. I would have rather seen this one as a set of bar graphs – the ‘tried it and liked it’ in the same color as the ‘haven’t tried it but want to do it’. Then the ‘never, and don’t want to’ can be lumped with the ‘tried it and didn’t like it’. Though I do wonder if the ‘tried it and didn’t like it’ might have been specific to the person they were trying it with on that occasion. It would be useful to know if those people would try it again.
I found the quote below so funny that I laughed out loud in the class where I was supposed to be serving as a TA rather than as an internet surfer. The class is taught by Paula England about Sex and Love in Modern Society, so looking at OKCupid’s blog was right on topic, but still. Laughing in class distracts the students.
“Religion is the opiate of the masses, so long as the masses are straight. However, amass a bunch of lesbians and you’re going to need actual drugs.”
Before anyone gets angry and posts to my blog, take a deep breath. Is it possible that straight people are claiming to be lesbians and then reporting drug use just to make lesbians look drugged out on OKCupid? Yes. But that’s a stretch. Is it possible that lesbians feel pressure to report being adventurous, thereby indicating an openness to drug use, if not actual use? Yes, it’s possible that they are reporting more drugs than they’re actually using or that they are the only honest people on OKCupid and all the straight people and gay men are under-reporting drug use. My point is that twisting Marx around like that was sociology nerd humor at it’s best.
OKCupid’s numbers come from 3.2 million dating profiles. Dating profiles may not be the place you’ll find soul-searching truths. However, what we do find are the embellishments people adopt to make their actual selves slouch closer to their ideal selves so as to attract their ideal mates.
Why draw attention only to the fathers? Clearly there must be quite a few unmarried mothers out there as well. I hope this isn’t suggesting that deciding to take a relationship into marriage is somehow only or primarily the man’s responsibility. Both women and men have agency around the marital decision. It would be nice if cultural constructs supported equal opportunity for popping the question…but headlines that emphasize men’s agency over women aren’t going to get us any closer to equality on that front.
It’s nice to see that this graph points out where definitions of racial categories change. It is also nice that it draws attention to the problem that many American children are being born into poverty or at least situations where resources are extremely constrained. In another graph elsewhere, the same group also reminds us that these births are largely NOT happening to teen parents.
The other critical point is that out of wedlock births are on the rise even though birth rates for teen mothers are declining. If in the past it was possible to think that the problem is just that teens are out having unprotected sex that leads to accidental births, we can no longer be so sure that this is what is happening. Age at first sex is decreasing which means that most of the people having children out of wedlock are capable of having sex without getting pregnant. They probably have been doing just that for years. Having children out of wedlock is best understood to be a choice, then, not an accident. Any efforts to prevent child poverty are probably not going to be successful if they rest on sex ed or free condoms (though I personally believe those things are important for other reasons). The American Heritage Foundation believes that if people would just get married, these kids wouldn’t be born into poverty. Others aren’t so sure it’s that simple.
What needs work
The problem with the write-up accompanying this chart is that it implies that the causal mechanism goes something like this: for whatever reason couples have children together but do not get married. The failure to get married means that these children will be far more likely to be raised in poor or impoverished conditions. For emphasis, I’ll restate: the parents’ failure to marry one another leads to children being raised in poverty.
Now. Here’s what I have to say about the chart. First, if that is the message, why not depict the out-of-wedlock birth rate by poverty status, preferably poverty status prior to pregnancy? I’d settle for poverty status at some set time – like the child’s birth or first birthday, but that isn’t as good. I feel like showing these numbers by race is subtly racist, implying that race matters here when what really matters is poverty, at least according to the story that they are telling and the story that many marriage scholars care about. Yes, it is true that poverty and racial status (still) covary rather tightly in America, but if the story being told is about poverty, I’d like to see the chart address that directly rather than through the lens of race. Furthermore, if race DOES matter, where are Asians? American Indians?
Moving away from the chart for a moment and getting back to the causal story, marriage researcher Andrew Cherlin finds that the causal arrow might go the other way. Being poor may be a critical factor in preventing folks from getting married. William Julius Wilson was an earlier proponent of this concept, especially with respect to poor African Americans. His work suggested that during and after the post-industrial decline in urban manufacturing jobs, African American men were systematically excluded from the work force and this made them appear to be poor marital material. Cherlin’s more recent work applies more broadly, not specifically to African American men, and bolsters the idea that marriage is something Americans of all backgrounds feel they shouldn’t get into until they are economically comfortable. What ‘comfortable’ means varies a lot, but most people like to have steady full-time jobs, they like to be confident that they won’t get evicted, that the heat or electricity will not be turned off, that they will have enough to eat.
The more important question would be: why don’t these assumptions apply to having children? Whereas getting married can represent an economic gain if you are marrying a working spouse, having children certainly does not (state subsidies do not cover the full cost of having children no matter how little the children’s parents make). Perhaps what we are faced with is people for whom getting married may not represent an economic gain. Marrying a person without a steady job could present more of a drain on your resources than staying single, whether or not you have kids.
This could easily be applied to just about all research, not just bench science.
What needs work
Why is it that the media believe their consumers to be so daft? Where did the sound bite come from and what has it done to the production of news? To the practice of scientific research?
What is missing from this depiction of the research ‘cycle’ is that some researchers interpret the pressure to turn complex reality into a series of sensational sound bites as a sign that they should alter the way that they write up results in order to better fit the media’s model of dissemination. It’s hard to say this is always a bad thing – if it means that scientists actively seek a more active role in the dissemination of their work in order to pursue a real discourse, it can be a good thing. If it means that researchers promote their results in a skewed fashion, fail to fully disclose/discuss the conditions in which their findings will hold, or start choosing projects based on what will be more likely to make the news, then this science news cycle can be sincerely detrimental.
Imagine looking at this information in a table. It would get the job done, but it wouldn’t have as much visual legibility as this graphic does. One thing I like about the graphic is that the illustrator was not impeded by the fact that sometimes there were ties for tallest or shortest. He just kept to the same paired down one tallest/one shortest depiction.
What needs work
I would have loved to see some indication of mean height. Does it fall in the middle, does the mean cluster towards the top? Does it cluster towards the bottom for some sports (like women’s gymnastics)? Even more interesting would have been changes over time. The human population has been getting taller on average so one would expect that athletes are also getting taller. But maybe some are not, like those in sports where the age of professionals is dropping (ahem, women’s gymnastics).
My apologies for the quality of the image – the scanner is refusing service this morning.
Lee, Jason. [illustration] (2010, 18 October) “High-Low: some all-time tallest and shortest athletes” in ESPN The Magazine. p. 64.
Regular readers, I had to close the comments on this post because I was getting spam comments faster than I could delete them (online gambling, mostly). If you are keen on commenting, email me and I will find a way to make sure your comments are heard. Wonder what the key word was that made this particular post such a spam magnet? Athlete? ESPN? Who can say.
About Graphic Sociology
Analyzing the visual presentation of social data. Each post, Laura Norén takes a chart, table, interactive graphic or other display of sociologically relevant data and evaluates the success of the graphic. Read more…