In my last post, I commented upon a graphic from the Philadelphia Inquirer where a min/max axis line would have been helpful. This post is a quick follow-up of sorts, because a week ago I flagged something similar for me to perhaps mention on Coffee Spoons. So here I shall mention away.
We have another graphic from the Inquirer in an article about the Philadelphia region’s oppressive humidity this summer. The chart presents its information straightforwardly—bars representing the percentage of hours wherein the dew point sat above 70ºF. Muggy. Muggy as hell. Because I guarantee you the heat in Hell is a humid one. None of the dry dessert heat.
Overall, the graphic works well. It is interactive so you can mouse over the bar and read the precise data point. I love that far more than the increasingly prevalent let’s-label-every-data-point-on-the-chart-and-distract-the-eyeball-from-the-actual-pattern-of-what-is-going-on approach.
This summer has been the third muggiest in Philadelphia in the last three-quarters of a century. The designer highlighted 2025 at the end of the series—not necessary, but I can live with it. But what then stands out are the two muggiest years—two very tall bars. But note that there is no axis line above them. No upper bound. Nothing to help inform the user what percentage point they approach.
I do not always use a maximum or minimum axis line, but usually the outlier has to be extreme, and in that case I will add extra lines around that point to give the user the vital context of scale. Otherwise, the outlier should be just a wee bit above or below the line. I thought I would find a relevant example in my work quickly, but it took nearly 20 minutes of reviewing old work to find one such example.
Here you can see in Figure 6 the pink line barely and briefly rises above the 80% maximum. The reader can see the value just pokes above 80% but was otherwise below it during the entire span of time. And that works great.
Again, this is a small critique of the mugginess chart, but I feel an axis line significantly helps the reader see just how muggy those summers were. Spoiler: nearly 54% of the time was “oppressive”.
To play devil’s advocate, perhaps if the article were not about how this is third muggiest summer, the designer could have skipped adding an axis line at 60% or so. But, because such the author placed such emphasis on the third-most bit, the graphic really would benefit from the context of how the 45% thus far for 2025 compares to the top-two summers.
Monday and Tuesday, Major League Baseball conducted its amateur player draft, wherein teams select American university and high school players. They have two weeks to sign them and assign them. (Though many will not actually play this year.)
Two years ago the Red Sox installed Craig Breslow as their new chief baseball organisation. He has cut a number of front office personnel and reorganised the Red Sox front office, leading to a number of departures. Crucially for this context, a number of the scouts who identified key Red Sox players like Roman Anthony were either let go or left. The team then focused on analysts and models.
My questions have thus been focused on how this might change the Red Sox’ approach to the draft. A running joke in Sox circles has been how every year the Red Sox draft a high school shortstop from California. But this year, the Red Sox’ first pick was Kyson Witherspoon, a starting pitcher from Oklahoma.
The graphic above shows how Witherspoon was ranked by the media who covers this niche area of baseball: a consensus top-10 pick. And yet the Sox selected Witherspoon at no. 15 overall. This has been another trend of the Sox over the last several years, where other teams select lower-ranked players and leave higher-ranked players available to the Sox and other mid-round selectors. Similarly, fourth-round pick Anthony Eyanson, ranked roughly 40–65, remained on the board and so the Sox took him at no. 87.
As someone who follows the Sox system, they need quality pitching prospects as they have very few of proven track records in the minors. Witherspoon and Eyanson provide them that, at least the quality, the track records have yet to develop. Marcus Phillips, seemingly, presents more of a lottery ticket. His ranking spread so far, from 13 to 98, it is clear there is no consensus on the type of talent the Sox took in him.
Godbout is a middle-infielder with a good hit tool, but light on the power. Clearly the Sox believe they can work with him to develop the power in the next few years. But all in all, three pitchers in the first four rounds.
Now, the additional context for the non-baseball fans amongst you who are still reading is this. Baseball’s draft does not work in the same way as those of, say the NFL or the NBA. One, the draft is much deeper at 20 rounds. (In my lifetime it used to be as deep as 50.) Two, teams (usually) do not draft for need. I.e., unlike the NFL where a team , say the Patriots, who needs a wide receiver might draft a wide receiver with their first pick, a team like the Red Sox who need, say, a catcher will not draft a catcher. A key reason why, it takes years for an MLB draftee to reach the majors if he does so at all. Whereas an NFL draftee likely plays for the Patriots the following year. In short, there is often a lag between the draft and the debut—unless you are the Los Angeles Angels. Thus you address your current positional needs via free agency or trades, not the draft. (Unless you are the Angels.) For the purposes of the draft, you therefore draft the “best player available” (BPA).
Some systems, however, are just better at doing different things. Some teams do a better job of developing pitchers, others of developing hitters. Some of developing certain traits of pitching or hitting. Some teams are just bad at it overall. The Sox have, of late, been very good at developing position players/hitters. They have been pretty not-so-great at developing pitching. Hence, when Breslow said he could improve their pitching pipeline, the Sox jumped at the chance to hire him. (It also helps everyone else they interviewed said no, and a number of candidates declined to even be interviewed.)
In part, the failure to develop pitching could be a failure to identify the correct player traits or characteristics. It could be the wrong methods and strategies, improper techniques and technologies. But, if we look at the recent history of Red Sox drafts, it could be, in part, also a consistent lack of drafting pitching. After all, the 26-man MLB team roster comprises 14 pitchers and 12 position players. (Technically it is a limit of 14 pitchers, but teams seem to generally max out their pitcher limit.)
You can see in my graphic above, since the late 2000s, the Red Sox, with few exceptions, ever drafted more than 50% pitchers. This period of time coincides with the ascendance of the vaunted Sox position player development factory and the decline of the homegrown starter. (Again, the obligatory reminder correlation is not causation.)
Nevertheless, in the last few years, we have seen the drafting of pitchers spike. In the first two years of the new Breslow regime, pitchers represent more than 70% of the amateur draft. (There is also the international signing period where players from around the world can be signed within limits. This is how the Sox have drafted very talented players like Rafael Devers and Xander Bogaerts. I omitted this talent acquisition channel from the graphics.)
Consequently, when a team states its strategy is to draft the BPA, but over 70% of all players selected are pitchers, I wonder how one defines “best”. Are the Red Sox weighing pitching more heavily than hitting? Is this an attempt to address a long-standing asymmetry in talent? In the models teams like the Red Sox use, are pitchers worth, say, 1.5× more than hitters? I doubt we will ever know the answer, though the team maintains they draft the best player available.
Ultimately, it may matter very little for the Red Sox in the near-term. The sport’s best prospect, Roman Anthony, is just starting to man the outfield for the Sox. A consensus top-10 prospect, Marcelo Mayer, has also just debuted. A top-25 prospect, Kristian Campbell, debuted on Opening Day. Two second-year players round out the outfield in Ceddanne Rafaela and Wilyer Abreu. A rookie catcher is behind the plate. The Sox may not need serious high-end positional player talent in the next 3–5 years. (Though it certainly helps when trying to trade for other pieces.)
But a two-year lull in drafting high-end positional player talent, on top of the previous two years’ first-round draft picks, catcher Kyle Teal and outfielder Braden Montgomery, being traded for ace Garrett Crochet, means the Sox may well have a several-year gap in positional player matriculation to the majors. That might matter.
Baseball, unlike the NFL and the NBA, is a marathon, however. So perhaps this is all a tempest in a teapot. Let us check back in five years’ time and we can see whether this new draft strategy, if it is indeed a strategy, has cost the Red Sox anything.
Thoroughbred racing is big business. And Philadelphia’s Parx Casino owns a racing track that, in a recent article in the Philadelphia Inquirer, has seen a number of horse deaths. The article includes a single graphic worth noting, a bar chart showing the thoroughbred death rate. The graphic contrasts rising deaths at Parx with a national trend of declining deaths.
Traditionally rate statistics are shown using dots or line. The idea is that a bar represents counting stats, i.e. how many total horses died. I understand the coloured bars present a more visually compelling graphic on the page, and so I can buy that reason if you are selling it.
Labelling each datapoint, however, with a grey text label above the bar remains unnecessary. They create sparkling, distracting grey baubles above the important blue bars. If you need the specificity to the hundredths degree, use a table. This graphic is also interactive. The mouseover state is where a specific number can be provided, adding an additional layer or level of depth in a progressive disclosure of information.
The Teamsters Union decided to officially endorse neither candidate in the 2024 US presidential election. Prior to their non-announcement announcement, however, the union surveyed its members and then released the polling data ahead of the announcement.
Of course, the teamsters represent but a single union in a large and diverse country. More importantly, the survey results reported only the share of responses for either candidate—and “Other”—so we have no idea how many of what number opted for whom. But hey, it’s another talking point in the final six weeks of the campaign.
Naturally, I decided to visualise the data.
The trend is pretty, pretty clear. The union’s rank-and-file clearly support Trump for president, with the exception of the teamsters in the District of Columbia. (Note, no survey was taken in Wyoming.) In fact, in only eight states plus DC did Harris’ support top 40%.
I thought three-dimensional charts died back in the 2010s. Alas, here we are in 2024 and I have to discuss one once again. have been following the Titan Inquiry this week and the opening presentation included this gem of data visualisation.
To be fair, I do not know how many designers, let alone specialist information designers, the US Coast Guard had or made available to create a clear and compelling chart and presentation, but…this is not it. First I will go through a number of points and then, when I had written about half of the post this morning, I decided it would simply be easier to put a white box over the main chart area and just recreate the graphic myself.
Unfortunately, after digging around, I could not find the actual dive depth data the Coast Guard used and so I essentially traced out the chart by hand. Not ideal, but for proof of concept as to how this chart could have been improved…I think my reinterpretation ssuffices.
To start, the chart sits on the slide with a drop shadow. Drop shadows are not all bad. They create perceived depth between an object and it’s background. The interwebs love them. I have used them. But I do not understand why here the chart needs a drop shadow to sit on the slide. Especially since the shadow pushes the chart “above” the deck, only for the three-dimensional bar chart to push the data “below” the chart’s surface, which means the chart data is being represented on the slide surface.
Deep breath.
The chart background features some kind of coloured gradient that became pixellated upon export and import into the PowerPoint deck.
The type was too small that it too became pixellated and grainy to the point that the dive labels are illegible. I would argue labelling each dive beyond its number is unnecessary in the context of Titan’s final dive, but without having listened to the presentation I cannot say for certain.
Next we have the third-dimension. It adds nothing and creates more coloured areas—because the dimension is fake, this a two-dimensional representation of three dimensions—that distract the eye from the important dimension, the length of the bar.
After that, we can look at the axis labels. First, there are far too many. Second, the maximum depth labelling makes no sense. Sometimes, if a line or a bar exceeds the chart maximum once or twice by a small amount, you can let it poke above the top—in this case bottom—line. If you know the rules, you know when you can break the rules. Here, however, the maximum label is 3800 metres.
But Titanic rests at 3840. Ergo 13 different measurements will need to sit below the chart’s maximum—minimum, technically—axis line.
Deep breath.
If she rests at 3840 metres, just add 60 to the chart minimum and you will ahve a final axis label of 3900 metres. Look carefully, however, and you will see in the bottom left how after the final white line, the chart keeps going. Clearly, the designers knew the chart needed more space. This unlabelled minimum is probably 3900 metres given the 100-metre increments used throughout.
But, however, if you add 160 metres to the chart you have a nice, round, divisible number of 4000, which means you do not need to mark the depths in 100-metre increments. It means all the bars sit within the chart. It means fewer pixels on the slide to distract the eyes. (Especially if you drop the background colour.)
Furthermore, if you look carefully at the green boxes, which represent successful dives to Titanic, you can see how the bars break the dimensional rules and are actually flat two-dimensional bars. Perhaps this was only noticeable to me as I worked off the downloaded file at a high-level of zoom to try and figure out the depths as precisely as possible. Or perhaps it is an artifact of the pixellated export of the graphic. If the latter, more of a reason not to make the thing a three-dimensional bar chart.
Then we can get to the colours.
Deep breath.
To start, red-green colour blindness is a thing. I harp on this often and so I will not rehash everything here. No, it does not mean all green and red combinations will not work, one just needs to be careful with them. This one comes pretty close to not working so I would have avoided it.
Secondly, just look at the red. I mean, how can you not. It is very bright and draws your eye almost immediately to all those red bars, particularly the one nearly a fifth of the way in from the right edge. That one is next to one of the successful Titanic dives. My first thought? Oh, that was the final dive. Wrong.
Red means non-Titanic dives. Again, I have not listened to the presentation, but these would presumably be dives of relatively less importance than the Titanic dives. I would not have made the less important dives the one colour that stands out the most.
If you want to go green represents successful Titanic dives and red represents unsuccessful Titanic dives, that makes sense. I can understand the design decision. (Though you would still need to ensure the shades work with each other.) In that case maybe the blue bars represent non-Titanic dives.
Instead, here blue represents unsuccessful dives to Titanic, which of course means the final dive, which of course includes the inquiry’s raison d’être. Not only that, the chart’s background is also blue, which makes visually separating the bars from the background more difficult. This is particularly true at the sides of the chart where the gradient leaves the darker blue.
Finally we have a little orange box with some tiny type pointing out the final dive’s depth. That bit, more visible than the green and orange bars, was still lost to me behind the red bars.
And breathe.
All in all, a mess.
As I noted at the top, halfway through I decided this was such a mess I would prefer just to show how the chart could have been designed. It took a little over an hour to make the chart. Clearly I do not have the chart style guidelines for the Coast Guard, so I just chose a typeface I think worked and then picked some reasonable colours from the deck.
Call me biased, but my design substantially improves the chart. First, you can read the text. Second, the colours fit the brand, do not distract from and in fact highlight the final dive. If I started from scratch, I would prefer to use what looks like the full content area of the PowerPoint slide, but I simply traced over the existing chart. I.e., ideally the chart would have been a little bit taller. I did have to cut out the labels for each dive, but as I stated earlier, they were illegible.
Credit for the original piece goes to the US Coast Guard.
As it happens, the Latino culture largely remains x’ed out on using the term Latinx, according to a new survey from Pew Research.
The issue of supplanting Latino/Latina with Latinx as a gender neutral replacement—or as a complementary alternative—emerged in the general discourse in that oh-so-fun year of 2020 when everything went well.
One common argument I have heard is the inherent gender within the Spanish language. Broadly you use -o for singular masculine endings and -a for singular feminine forms and -os for plural masculine and mixed gender forms and -as for plural feminine forms.
Perhaps my biggest issue is that -x does not linguistically make sense. X is typically pronounced like a j or sometimes an s. Consider how Mexicans pronounce Mexico, May-hie-co. Latinx becomes La-teen-h, an almost silent ending that does not fit, at least to my ears. Pero, hablo solo un pocito Español. Aprendí a hablar por cuatro años en la escuela, dos años de niño, y trabaja en una cocina del restaurante. Thus Latinx, pronounced Lat-in-ecks, always seemed, daresay, a gringo solution to a problem that earlier polling of Latino communities did not indicate was a problem. With the potential exception of the young, but even then not terribly so.
Four years later, however, and not much has changed according to Pew. Their graphic shows as much.
Significantly more people are aware of Latinx as a term. Fewer people use the term, though not significantly. Although a shift from four to three percent can be seen as significant given its low adoption. Moreover, as a second graphic shows, more people who are aware of the term think it should not be used.
The article continues with a discussion of a new new alternative, Latine, which to my ears makes more sense. But is largely yet unheard of in the community—20%—and of those who have heard it, almost nobody uses it.
As far as the graphics go, I am not a huge fan.
For the first, we have two lines showing the movement between two datapoints. At the most basic level, the use of a line chart makes sense to depict two series moving between two points in time. But without any axis labelling one can only trust the lines begin and end at the correct position. Furthermore people need to read the specific labels to get a sense of the line charts’ magnitude. More of a tell, don’t show approach. If the chart had even a simple 0% line and 50% line, one need not label all four datapoints to convey the scale of the graphic.
Ultimately, though, does a chart with four datapoints even need to be graphed? Some would argue in most instances a dataset with fewer than five or six numbers need not be visualised; a table should suffice. Broadly I agree. This chart does show a particularly striking trend of increasing awareness of the term, but largely static to declining usage.
The second graphic, however, falls more squarely into that argument’s camp of “Why bother?” It shows simply two numbers. Numbers placed atop purple rectangles. Without any axis labelling, we presume these bars represent columns encoding the percent—at least the lines in the first chart were clearer to their meaning. Then we still have the issue of telling and not showing. Perhaps labelling to the left from 0% to 75% or 80% would help. Then you need not even add additional “ink” with the four digits sitting atop the bars and sparkling for unnecessary reader attention.
This falls into a broader trends I have witnessed over the last few years in the information design and data visualisation field of labelling individual datapoints within a chart. It is a trend with which I strongly disagree, but perhaps is best left for another post another day. Suffice it to say, if knowing the precise measurement is important, a chart is not the best form. For that use case I would opt for a table, best used to organise and find specific datapoints.
Overall, Pew shows that within the Latino community, very few use the term Latinx. Consequently, perhaps this entire post is, to use a Spanish-language expression, a tempest in a teapot.
Last night I went to see Top Gun: Maverick, the sequel to the 1986 film Top Gun. Don’t worry, no spoilers here. But for those that don’t know, the first film starred Tom Cruise as a naval aviator, pilot, who flew around in F-14 Tomcats learning to become an expert dogfighter. Top Gun is the name of an actual school that instructs US Navy pilots.
Back in the 1980s, the F-14 was the premiere fighter jet used by the Navy. But the Navy retired the aircraft in 2006 and it’s been replaced by the F/A-18E/F Super Hornet, a larger and more powerful version of the F/A-18 Hornet. So no surprise that the new film features Super Hornets instead of Tomcats.
And so I wanted to compare the two.
The important thing to note is that the Tomcat flies farther and faster than the Hornet. The F-14 was designed to intercept Soviet bombers that were equipped with long-range missiles that could sink US carriers. The Hornet was designed more of an all-purpose aircraft. It can shoot down enemy planes, but it can also bomb targets on the ground. That’s the “/A” in the designation F/A-18. In the role of intercepting enemy aircraft, the F-14 was superior. It could fly well past two-times the speed of sound and it could fly combat missions over 500 miles away from its carrier.
In the interception role, however, the F-14 had another crucial advantage: the AIM-54 Phoenix missile. It was a long-range air-t0-air missile designed for the Tomcat. It does not work with any other US aircraft and so the Hornet uses the newer AIM-120 AMRAAM, a medium-range air-to-air missile.
There are plans to design a long-range version of the AIM-120, but it doesn’t exist yet and so the Hornet ultimately flies slower, less distance, and cannot engage targets at longer ranges.
However, dogfighting isn’t about long-range engagements with missiles. It’s about close-up twisting and turning to evade short-range missiles and gunfire. And even in that, the F-14 could use four AIM-9 Sidewinder missiles whereas the F/A-18 carries only two on its wingtips.
By the 2000s F-14 was an older aircraft and while the moving, sweeping wings look cool, they cause maintenance problems. They were expensive to maintain and troublesome to keep in the air. But they are arguably superior to what the Navy flies today.
Moving forward, the Navy is beginning to introduce the F-35 Lightning II to the carrier fleets. Maybe I’ll need to a comparison between those three.
Friday the Bureau of Labour Statistics published the data on the jobs facet of the American economy. Saturday morning I woke up and found the latest New York Times visualisation of said jobs report waiting for me at my door. The graphic sat\s above the fold and visually led the morning paper.
Almost out of the hole.
We have a fairly simple piece here, in a good way. Two sections comprise the graphic. The first uses a stacked bar chart to detail the months wherein the US economy lost jobs during the previous two and a half years. We can take a closer look in this second photo that I took.
But the recovery hasn’t been uniformly good for all.
Here we can see the stacked bars pile up with the most recent bars to the right. Some of the larger bars have labels stating the number of jobs either lost (top) or gained (bottom). I’m not normally a fan of stacked bar charts, because they don’t allow a reader to easily discern like-for-like changes. In this instance, the goal is to show how close all the little bits have come towards making up the three negative bars. Where I take issue is that I would prefer the designers used some sort of scale to indicate even a rough sense of how many jobs the various bars represent.
That issue crops up again to a slightly lesser degree with the bottom set of graphics. These compare the growth of hourly earnings and inflation both from February 2020. During the first few months of the pandemic and its recession, you can see earnings for those most directly impacted by shutdowns drop. But there is no negative scale accompanying the positive scale and that makes it difficult to determine just how far earnings fell for those in, say, leisure and hospitality.
The second part of the graphic works overall, however it’s just some of the finer design details that are missing and take away from the graphic’s overall effectiveness.
This all fits part of a larger trend in data visualisation that I’ve been noticing the last few months. Fewer charts seem to be using axes and scales. It’s not a good thing for the field. Maybe some other day I’ll write some things about it.
For this piece, though, we have an overall solid effort. Some different design decisions could have made the piece clearer and more effective, but it still does the job.
Credit for the piece goes to Ben Casselman, Ella Koeze, and Bill Marsh.
I noticed an interesting thing this morning. Over the holiday weekend I bookmarked a BBC News article about new airlines because it included a small graphic showing the number of airlines started during the pandemic (32) and the number of new airlines lost during the pandemic (55). The graphic used a stock three-dimensional illustration of a passenger airlines with a blank white body. From the top of the body rose two white bars, next to the left was the shorter of the two with a 32. The right was taller and had a 55. Above each was a header saying something to the effect of “Airlines started in 2020” and “Airlines lost in 2020”, respectively. Funny thing this morning that when I returned to the bookmark with this post in mind, the article’s graphic had disappeared.
This weekend I happened to start re-reading 1984, George Orwell’s classic dystopian novel about a man named Winston Smith. He works in the Records Department and is tasked with “rectifying” misstatements. I had just finished reading the section where Orwell describes Smith’s work wherein he takes previously published newspaper articles about statistics and figures and then edits them to include new numbers aligned with the actual outputs. This way should anyone read the old article for evidence of a previous past, they find the output forecasts have always been correct. He then destroys the written record of the old past by dumping it into a memory hole, a pneumatic tube that delivers it straight to a furnace where the old past is incinerated and thus replaced with Smith’s new version.
When I read the article again, because the graphic was gone, I read a paragraph that had figures for 2021. I cannot recall those numbers being present earlier this weekend. But they are roughly where I remember the old graphic being. Yet the article includes no note about any edits to a previous version let alone what those edits may have been. And so now I am left wondering if I really saw what I think I remember that I saw. How very Orwellian.
But let’s assume I did see what I thought I saw, the graphic was actually unnecessary. It presented two figures, 32 and 55. The bar chart itself had no axis labels and that made it a bit difficult to believe the numbers themselves. It did not help that the white bars blended almost seamlessly into the white body of the airliner. Moreover, the graphic was large and fit the full width of the text column. For two figures.
My initial goal was to show this graphic I made to show just how little space truly needs to be used to show an effective graphic. I also changed the direction of the bars. Instead of making one bar about the positive change and the other the negative change, I made both bars about the change. Therefore the one bar moved upwards with the positive (32) and the other downwards with the negative (55). I then plotted a dot to show the net change between the two. Yes, 32 airlines were created in 2020. But that still made for a net loss of 23 that year.
But because the graphic was missing and there was some new text for 2021 figures, I decided to incorporate them as well to show how the trend basically continued year over year.
Finally, a graphic
I left the white space to the right to illustrate how you really do not need a full-width graphic to display only six data points, itself a three-fold increase on the original graphic’s data content. The original graphic contained more illustrated plane than it did data content.
Graphics should be about the data, not about the splashy, flashy, whizbang background content that ultimately distracts our attention away from what should be the focal point of the piece: the data. The article still contains photos of planes with the livery of the new airlines, of empty terminals to represent the pandemic losses, and portraits of executives. This graphic did not need an illustrated plane taking over the graphic. It needed to only show those two numbers.
I would even contend that the article could have made do with a simple factette, two big numbers. Airlines closed in 2020 and the airlines opened. It need not be fancy, but it quickly delivers the big numbers with which the reader should be concerned. You don’t need to see an aircraft or a terminal. You could add some colour to the numbers or even a minus sign as there is a significant difference between a 55 and a -55. But all in all, the graphic need not be full width like it was originally.
But I think we should all keep in mind the value of transparency. The graphic did exist, of that I am certain. But future readers or even my sanity cannot be sure that it did. And in an era where “fake news” and fact-checking are important, I wonder if we need to be including corrections notes in more of our news articles. Because if we lose faith in our news, we have little left to lean upon in our societal discourse about the events of our time.
The Wall Street Journal put together a nice piece about the uptick in elementary school shootings, both in the number of shootings and the number of deaths. It used two bar charts, regular and stacked, and a heat map to tell the story. The screenshot below is from a graphic that looks at the proportion of school shootings that occur at elementary schools. They are not as common, but as other graphics in the article show, they can be quite deadly.
Not a great trend…
The graphic above does a nice job of distilling the horror of a tragedy into a single rectangle. That is an important task because it allows us to detach ourselves and more rationally analyse the situation. Unfortunately the analysis is that yes, Virginia, things really have been getting worse.
Overall the article is simple but soberingly effective. School shootings are a problem with which American society has not dealt and my cynical side believes with which we will continue to not deal.
Credit for the piece goes to James Benedict and Danny Dougherty.
