"Guns are Bad News for Women?" Huh ... - Part IV

In Part I, Part II, and Part III, I have disputed mikeb's claim using only the dataset that he used, albeit, I have updated the numbers to 2006 and looked at states individually as opposed to as a whole (the only change was I added DC). From this point forward, I plan on using the full 50 state dataset with the District of Columbia.

So, to begin, let me address the DC issue. It is frequently left out of gun control statistics without any explanation. From the tables I showed in Part III, we see that DC frequently is an outlier for the dataset we are looking at (2006 Deaths of Women). For this limited dataset, I don't see the logic. It actually helps support mikb's position for suicides and accidents (since DC has no female firearm suicides or accidents). But there is that homicide number, although I showed that even though DC has a homicide rate higher than 8 of the high gun states, adding it in to the low gun states doesn't change the values much (and it is more honest to look at it this way). So by leaving DC out, one truly is cherry picking the data.

What reasons would there be to leave DC out? To begin, unlike all of the other states, it is not a state, just a city. So where a state is a mixture of cities, subburbs, and rural areas, DC is only a city. But one could also make an arguement that Rhode Island and Conecticut are very nearly just cities. Furthermore, someplaces like Massachusetts have a population dominated by their major city. Therefore, I don't buy that excuse. If you are going to use that excuse then at least you should include the DC numbers in with Maryland or Virginia. Maryland has the lower gun ownership so I would say it belongs there. And you would get something like this:

2006 Death Rate of Women (per 100,000) DC, MD, VA
	DC	MD	MDdc	VA	VAdc
Firearm Ownership	3.8	21.3	19.6	35.1	32.8
Firearm homicide	2.27	1.35	1.44	1.23	1.31
Other homicide	2.59	1.49	1.60	1.11	1.22
Total	4.86	2.84	3.03	2.34	2.53
Firearm suicides	0.00	0.73	0.66	2.06	1.91
Other suicides	1.94	2.63	2.56	3.24	3.14
Total	1.94	3.36	3.22	5.30	5.05
Firearm accidents	0.00	0.00	0.00	0.00	0.00
Other accidents	25.58	18.01	18.74	24.80	24.86
Total	25.58	18.01	18.74	24.80	24.86

As you can see, the numbers don't change much (but you can go to sleep at night knowing you didn't purposely obfuscate the data).

So lets see how mikeb's hypothesis holds up when we look at the entire United States. All of the charts show the rate on the y axis and the states on the x axis (denoted by their ownership percentage). First, women firearm homicide rates:

Wow, is that a trend or a drawing of a set of shark teeth? Seriously, how can you say there is a trend. Sure you can draw a line in there, but you could draw a whole bunch of different lines that would all have the same average delta between the point and the line. Real quick we see that on the high gun side, there are five states with women firearm homicide rates above 2. SC, LA, AL, MS, and WV. Is it a coincidence that four of the five are in the south (and WV is pretty close to them)? The only trend I have seen in this data is that as the number of datapoints increases (from 2 to 17 to 51), the predicability of the hypothesis decreases (in other words, it is wrong). If a hypothesis were correct, then increasing the datapoints should increase the predictability. Frankly looking at this graph, if a state increased its gun ownership to 60%, there is no telling where they would be (although it is pretty safe to guess it wouldn't be above 2.5).

Let's move on to suicides:

OK, there might be some hope for the hypothesis. There appears to be a threshold around 2o% ownership. Below this, the number of gun suicides decreases dramatically (duh...if they don't have guns they can't kill themselves with guns). Above this threshold there will be a gun suicide rate of at least 0.75. What this tells me is the place to do some further study is around this threshold with respect to other methods of suicide (perhaps 20% is universal - if you only allow 20% of the bridges to be jumped off, will people abandon trying to jump off of them). After this threshold, there is no predictive ability again, the datascatter is as chaotic as homicides.

Finally, we have accidents:

This is the most intersting of all. There appears to be a threshold again (like suicides) at around 40% where the accident rate never goes above 0.10. However, above 40% there are several states that still have a 0.00 accidental death rate for women. In general, you can see that accidents increase above the 40% threshold, but not universally (again, this is a no-brainer). Remember the qualifier I had about training and usage. What really needs to be examined here is the 0 rate states. Why do low gun states like MA, CT, and RI have no accidents? My hypothesis would be since they have driven out the majority of gun owners, only the most die hard (competent, trained, etc) continue to own guns legally. They are the ones handling them with expert care and going to the range regularly to hone those skills, hence no accidents. The non-criminals who own "illegal" guns never get them out (for fear of the law) hence don't have a chance to have an accident. Accidents happen through use, not ownership. Likewise, why are Wyoming and Mississippi high on the accident list, but Utah and Wisconsin are not? All four have high gun ownership rates. Once again, one would have to look at two things which are beyond the scope of this study: absolute number of firearms (not just number of owners) and usage of firearms.

This last point brings up an interesting data error. All of this dataset is based on firearm ownership rates. I previously discussed some of the inaccuracy inherent in the reporting of firearm ownership. The sorting of states by total firearms owned (hence chances for a firearm to cause harm) might produce a very different result. For example, based on JayG's Friday Gun Pr0n (for non gunnies, its OK to click the link, the only nakedness you will see is metal), I am fairly certain that he has an armory that could safely be used by most of western Massachusetts, with some to spare. However, I have a relative in high gun ownership Utah, that only has a single firearm. Since this study only looks at firearm ownership, they both count the same. I don't know that there has ever been an attempt to determine how many guns are in each state. Think of gun owners as the Senate, and guns as the House of Representatives: JayG would be California (sorry for the insult) and my relative would be Alaska. I do suspect that any survey would be about as accurate as the ownership percentages for the same reasons: people don't want to tell you. I may later do a hypothetical based on gun repressed states hoarding more guns per owner than free states. But for now, ownership will have to suffice (with the caveat that we remember in the end result, our numbers have error in them).

To summarize, as we have expanded out the data set to all 50 states and DC, we find that mikeb's hypothesis breaks down even further, for all areas. But I am not finished yet, not by a long shot (I've only made 4 tables and 3 graphs). On to Part V.

"Guns are Bad News for Women?" Huh ... - Part III

In Part I and Part II, I have discussed the basis of mikeb hypothesis that "guns are bad news for women." I ended Part II with three questions yet to answer. Going back to the original table, mikeb and Hemenway posit that the data prove more guns equates to more death for women. I created an updated table based on rates in Part II. My numbers correlate well with Hemenway's. So why don't I agree with his conclusion?

First, the table contains two datapoints - high gun states and low gun states. It so happens that looking at the extremes of gun ownership, states with more guns have more homicides and suicides. So let's not stop there, let us break out the data and look at individual states, that will then give us a total of 17 data points. If mikeb's hypothesis is correct, then we should see an increasing trend among the high gun states (as % ownership goes up), and a decreasing trend among low gun states (as the % ownership goes down).

2006 Death Rate of Women (per 100,000) High Gun States
	KY	ND	AL	AR	ID	MS	WV	SD	MT	AK	WY
Firearm Ownership	47.7	50.7	51.7	55.3	55.3	55.3	55.4	56.6	57.7	57.8	59.7
Firearm homicide	0.84	0.00	2.45	1.88	1.24	2.61	2.38	0.25	0.42	0.92	0.77
Other homicide	1.26	1.58	1.35	1.88	0.69	1.94	1.41	2.02	1.69	1.23	0.39
Total	2.09	1.58	3.80	3.77	1.92	4.55	3.79	2.28	2.11	2.14	1.16
Firearm suicides	2.09	1.26	2.32	1.60	2.20	2.41	2.81	2.02	1.06	3.06	2.70
Other suicides	2.89	4.10	1.73	2.79	3.71	2.41	3.03	3.29	4.23	6.43	6.17
Total	4.98	5.36	4.06	4.40	5.91	4.81	5.85	5.31	5.29	9.50	8.86
Firearm accidents	0.09	0.00	0.30	0.14	0.14	0.27	0.54	0.00	0.00	0.31	0.39
Other accidents	40.03	30.56	36.50	33.84	32.71	40.72	45.36	41.73	41.65	25.42	37.77
Total	40.13	30.56	36.8	33.98	32.85	40.99	45.9	41.73	41.65	25.73	38.16

For high gun states, we don't see a correlation (trend) between gun ownership and homicides. Same for suicides and same for accidents. So lets look at low gun states:

2006 Death Rate of Women (per 100,000) Low Gun States
	DC	HI	NJ	MA	RI	CT
Firearm Ownership	3.8	8.7	12.3	12.6	12.8	16.7
Firearm homicide	2.27	0.47	0.72	0.27	0.91	0.84
Other homicide	2.59	1.42	1.02	0.87	1.09	1.00
Total	4.86	1.90	1.74	1.15	2.01	1.84
Firearm suicides	0.00	0.47	0.18	0.39	0.55	0.22
Other suicides	1.94	4.58	2.41	3.50	2.19	3.12
Total	1.94	5.05	2.59	3.89	2.74	3.35
Firearm accidents	0.00	0.00	0.07	0.00	0.00	0.00
Other accidents	25.58	23.06	20.35	24.92	28.64	24.88
Total	25.58	23.06	20.42	24.92	28.64	24.88

Again, same result, there is no correlation(trend). Even if we ignore DC, there is still no correlation. So the hypothesis fails when more than two data points are looked at (using the exact same set of data).

Comparing the two, the low gun states in general have lower homicide rates than the high gun states. Except for SD and ND which have lower rates than all of the low gun states. And MT is lower than all but 1 low gun state. Interestingly enough, SD, ND and MT are contiguous to each other. Which leads us to the first major problem with Hemenway's table: Simplified conclusions (such as mikeb's) only work if all other variables are equal. In this case they are clearly not.

Hemenway and mikb make the mistake of using only a 2 datapoint set to formulate a conclusion. With only 2 datapoints, no outliers or exceptions are identified. Once the same data to make the 2 datapoints is taken back to its original 17 datapoints, at least 4 outliers (the 3 mentioned above and DC) begin to emerge for homicides alone. Whenever one is examining a dataset, you cannot ignore the outliers. You may decide not to include them in your dataset (DC) but you must provide a valid reason for the expulsion. By crunching the numbers down to only 2 datapoints, Hemenway and mikeb cover up the datapoints that go contrary to their hypothesis.

The United States is not a homogenous society. I complain about California drivers and Boston drivers. I have never complained about Oklahoma or Texas drivers. Rhode Island and Utah have very homogeneous religious makeups. Most every other state does not. North Dakotans don't have problems with punch card ballots. Floridians do. The simple fact is, people (in general) act differently depending on where they live. Even within a state, people are different in different counties (like the Texans who can't stand people from Dallas). So to simplify an issue like homicide and guns in the whole nation and assume that gun ownership is the major factor contributing to it is dishonest. Looking at the datapoints I see three distinct regions that have very similar numbers: 1) the previously mentioned ND, SD, MT and I'll add in WY, make a contiguous region that has firearm homicide less than 0.8. 2) AL and MS are next to each other and have very similar homicide rates. 3) MA, CT, RI, and NJ are all right next to each other and while MA firearm homicide rate is about 1/3 the rate of the other three states, the non-firearm homicide rate is very similar. So, 10 of 17 of the data points fall rather neatly into a regional category. Perhaps then this has more of an influence than firearm ownership? I'll have to look at that.

Next let's compare suicides between the two tables. Unlike with homicides, there are no obvious firearm outliers. All of the low gun states have lower firearm suicides than the high gun states, so one could safely conclude that states that have access to more guns see more people use guns for suicide. But isn't this stating the obvious? What the real question is, is whether the overall suicide rate would decrease if the availability of firearms decreased. Looking at the non-firearm rates and overall rates we do see a few outliers: 1) HI has a overall suicide rate higher than 4 of the high gun states, and it has a higher non-firearm suicide rate than all but 2 of the high gun states; 2) AL is the only state of the 17 that has a non-firearm suicide rate lower than the firearm suicide rate (although their neigbor MS is equal); 3) DC has a suicide rate far lower than any other of the 17 states; 4) AK and WY (the highest gun states) have firearm suicides that are not much different than the other high gun states, but their non-firearm suicide rates are 50% more than the next highest state.

Since I saw a potential for regional influence on homicides, let me look at suicides as well. The four northeastern states have a nice cluster of rates that are similar. AL, AR, and MS have more variation in their firearm suicide rates, but the total suicide rates match up well. Finally, SD, ND, MT and ID this time have a similar situation (overall suicide match well, even though firearm suicide have a disparity).

Finally, accidents. The first thing that should jump out at you is that there are no firearm accidents in low gun states (except New Jersey). Even more fascinating is that there are no gun accidents in ND, SD and MT (hey that regional thing pops up again! - I may be on to something). AL and MS once again have similar firearm rates.

So to sum up what I have looked at, the numbers for the states that make up the high gun and low gun states do not mesh well with the hypothesis of more guns = more homicides, suicides, and accidents. There is no trend. In general one can conclude that there are more firearm homicides, suicides, and accidents in the states that have the most guns compared to the states that have the least guns. But this does not mean that guns are the cause (if that were the case we should be seeing a trend).

The other theme that kept popping up is that certain regions of the country have similar numbers. This is something I will have to explore more to answer the hypothesis.

So on we go to Part IV

"Guns are Bad News for Women?" Huh ... - Part II

In Part I, I introduce mikeb's hypothesis that "guns are bad news for women" Let me now get into some statistics. Hemenway's table that mikeb provides has absolute numbers High Gun States and Low Gun States. Since the numbers are supposedly from 2003 and I don't know what criteria for high gun states or low gun states was used, I set about to recreate the table using rates (per 100000) so that numbers could be compared independent of population.

First, all homicide, suicide, and accident information was taken for the year 2006 using the CDC WISQARS database. Only fatalities were examined (I might do accidents another time). I included all homicide and legal intervention (cops shooting bad guys) in with homicide. Second, for the firearm ownership rates, I used the 2001 Behavioral Risk Factor Surveillance System in North Carolina which surveyed more than 200,000 people nationwide. One thing to note about gun ownership, there is not an accurate survey out there. All of them are based on people reporting, and people reporting have varying reasons why they would not answer truthfully. For example, some may say they have guns when they don't because they are suspicious of someone scoping out their place, some may say they don't have guns when they do because they are suspicious of someone scoping out their place, some may say they don't have them when they do because they are criminals, some may say they don't have them and they do because it is illegal to own what they have (i.e. cities with gun bans), and on and on and on. At best, the numbers from this survey are an indication of the legal firearms ownership only. So, from this we should realize that my data (and Hemenway) is tainted with inaccuracy from the start.

With this data I sorted it by gun ownership and came up with a list of High Gun States and Low Gun States that is similar to the one mikeb presents. So I know I am on the right track. The one difference is that District of Columbia is not included in the Low Gun States list. This is usually the case for many studies that are trying to show that guns are bad. DC has the lowest gun ownership rate in the nation, yet it is almost always on the high end with most crime statistics (obviously the criminals didn't realize they aren't suppose to have those guns). In this instance, omitting DC doesn't hurt the cause much since we are looking at guns and women (men by far commit more murders, have more suicides, and more accidents than women). The population of the samples is still about even (High - 10,866,675 women; Low - 11,032,622 women). Here is the table of the rates with and without DC.

2006 Death Rate of Women (per 100,000)
	High Gun States	Low Gun States	Low Gun States (no DC)
Firearm homicide	1.67	0.64	0.60
Other homicide	1.46	1.04	1.00
Total	3.13	1.69	1.59
Firearm suicides	2.16	0.28	0.29
Other suicides	2.92	2.95	2.98
Total	5.08	3.24	3.27
Firearm accidents	0.93	0.03	0.03
Other accidents	37.87	23.18	23.11
Total	38.8	23.2	23.14

A couple of items for thought. First, in this instance why bother excluding DC? The rates come out virtually the same. Second, why did Hemenway/mikeb not list the Other Accident deaths? I have three theories on this. 1) Because accidental deaths by firearms are so small (especially when looking only at women) that statistically it is a non-issue (however, I would argue that we could reduce those accidents through more training - on the other hand, you can't eliminate them, people still have the right to be boneheads). Putting the non-firearm accidents would detract from the conclusion that Hemenway is trying to get you formulate. 2) Pulling this number from WISQARS requires a calculation and whoever gathered Hemenway's numbers didn't realize this. You can't do an autosort for non-firearm accidents, it is an undefined category. So I grabbed the total accidents and subtracted the firearm accidents and presto, you have the non-firearm accidents. 3) Whoever compiled the information was sloppy. This could have been a completely unintentional oversight. However, if it was, it was sloppy. Whenever you are comparing numbers or categories, you want to make sure that you have apples to apples comparison. In this case, ommitting the non accidental firearm deaths might lead someone to believe that you are hiding something.

So, how can these numbers be explained? Once again, if you believe that guns cause each of these (see Part I), then you're done. Go write a book and start getting grants from the Joyce Foundation, they are always looking for new shills. If, however, you actually care about reducing each of these, then we need to look at each individually. Remember, the hypothesis that mikeb put forward is that guns are bad for women and that guns in the home cause more violence towards women.

Starting with accidents, we can pretty much discount the second part of the hypothesis since accidents cannot be considered violence. Its unintentional. No one was trying to harm anyone. As for the first part, well, this is actually expected. More guns without the proper training means more accidents. Not only that, but more handling of guns (without training) means more accidents. But it won't always be documented as such. For instance, I would be willing to bet that if you armed every single person in DC with guns (that were illegal to own previous to Heller) you wouldn't have their firearm accident rate change one bit (0 per 100,000). Why? Because if someone got shot, how would it be reported? If it is reported as an accident then the person who had the gun is now in trouble with the law for having an "illegal" gun. If it is reported as an assault, it becomes another unsolved crime in a city full of violence. Meanwhile in North Dakota, where they have lots and lots of guns and handle them regularly (i.e. they are not hidden away in a drawer in case someone breaks into their inner city apartment - never seeing any range time), the accidental firearm death rate is also 0.

Next we have homicides. Relatively few guns bought at pawn shops, retail stores, or gun shows are used in crimes. The Bureau of Justice Statistics estimates that 80% of guns used in crimes are from family, friends, a street buy, or illegal sources. This jives nicely with the FBI statement that 80% of crime is gang related. All of these guns couldn't be guns in the home (and the statistics above would indicate that as much as 80% weren't). So the second premise is shakey again, up to 80% of the women killed are not killed by legal guns in the home (which is what the high and low states are categorized by). I'll discuss the first premise later.

Finally, suicides. This can be an emotional subject for some. Most people know someone who has committed suicide. However, whether a person shoots themself in the head or slits their own throat, the suicide is no less horrific. As with homicides, the CDC does not record where the firearm came from that was used. However, we can probably safely assume that people with access to firearms with choose firearms in a higher proportion than people who don't have access to firearms (that is common sense). Some people really want to kill themselves. Some people just want to cry out for help. Those who want to kill themselves will choose the most lethal method (guns, poison, jumping off of high buildings), those who want to cry out for help choose less lethal means (overdose, self asphyxiation, slitting wrists). To examine suicide and firearms we will have to look at our dataset further.

So up to this point we have two parts of the hypothesis and three types of death - a total of six items to evaluate. I have already shown that it is of no use to evaluate accidents for either one of the premises and that the second premise is faulty for homicides. That leaves three items to explore:
1) Are guns bad for women with respect to homicides?
2) Are guns bad for women with respect to suicides?
3) Do guns in the home cause more lethal suicides?

Tune in to Part III for more analysis.

"Guns are Bad News for Women?" Huh ... - Part I

There is a blog that I have begun commenting on regularly after being directed there from another blog that I read. The author takes a strong stand for gun control for the safety of society as a whole. In spite of having facts presented to him which show his theories are wrong, he refuses to believe them and rarely provides any facts to back it up.

Recently he wrote a post about how "guns are bad news for women". You'll have to read his post to make some sense of the rest of this blog, as I don't want to re-post it here. As part of it he includes a table from David Hemenway's book "Private Guns Public Health." This table he cites as the proof to show that guns are bad for women. Since I am on a business trip with nothing to do in the evening, I thought I would take some time to dispute the position that he has taken. First let me make some objections to his conclusions.

"But what it [the table] shows is that where there are guns, there are more incidents of gun violence"
Actually, what this table shows is that the same tool (a firearm) can be used to create death in a variety of ways. And that when there are more of that tool, then there are more of those deaths.

"It's a sad fact that in America, women are brutalized by men too often, but what this chart shows is that when there's a gun in the house, it becomes lethal."
1) America isn't the only place in the world where men brutalize women. It's a sad fact everywhere. 2) If one women is brutalized it is too many. 3) This chart doesn't have anything to do with a gun in the home. The data set used does not take into account whether the gun that was used in the incident was in the home.

"The total figures on suicides indicate that the gun is especially effective."
This is actually a well known fact, guns are much more effective for committing suicide than many (not all) other means. What that tells me is that if someone wants to kill themselves, they use a gun; if someone wants to cry for help/get attention, they use a less lethal means.

The problem that Hemenway and mikb have is that they assume that guns are the cause of three problems with very different causal factors and then advocate removing the guns to solve the problem. So let's go through some logic.

Guns are inanimate objects. They can cause nothing. If left alone (even loaded), they will remain in that position until they have deteriorated away. I have a bed in my house, almost every time I lay down on it I go to sleep. Most Americans have the same issue, yet we would be absolutely foolish to say that the bed causes us to sleep. Our bodies cause us to sleep. Likewise we wouldn't even suggest that people without beds don't sleep.

Guns are tools. They have been specifically designed to propel a small piece of lead at high velocities in a mostly straight line (neglecting gravity). Like many other tools they have been used to provide food, entertainment, relaxation, and mayhem. People's fists have too.

So lets briefly go over the three areas that are in this table. Homicide is where one person kills another person. This is an act of anger or rage. Biologists have found that most species on the planet are reluctant to kill one of their own. Studies by the US military found the same thing and have spent decades conditioning soldiers to override this innate programming. We have become very effective.

Suicide is when someone kills themselves. Almost 75% more people die from suicide than die from homicide. More than 90% of people who attempted suicide or committed suicide had a mental illness (this includes depression).

Accidents happen. Sometimes it is from lack of knowledge, sometimes it is from carelessness. The more of something there is that are involved in accidents (cars, guns, matches, etc) without the corresponding training (notice that qualifier), the more accidents there will be.

If guns were the cause of all three of these, or even a major contributor, then the simple removal of guns would drastically decrease or eliminate these problems. It is obvious to state that removing all guns would eliminate all gun murders, gun suicides, and gun accidents. If gun murders, suicides, and accidents are much more nefarious than other types of murders, suicides, and accidents then eliminating them might (notice the qualifier) be advantageous. However, if the problem does not lie with the inanimate object, but the person wielding that object than all elimination would do is change the object. The problem still remains.

More in Part II.

More Firearm Motivational Posters

I had a few moments before the fireworks last night and whipped together a few more motivational posters.

First, the kids are learning about Egypt so this one seemed appropriate.


I love the Saiga-12, and what better than to have their AK version slung on your back as a backup.


Of course, a tribute has to go out to all of those who carry a full size .357 Magnum.


Some people think it is to prevent black eyes, others ...

And to finish it off, one to continue the play on the pageant theme. Fifteen years ago when my wife was competing in pageants, I bet she never in a million years thought she would be posing with her crown and an intermediate caliber (medium powered) rifle.
My wife viewed all of these and gave her approval with giggles!

Motivational Posters and Sarah Palin

When the first motivational poster came out, they probably made people feel good. Then we all wised up to the fact that if you need a poster to feel good, you have some serious problems. So parody of them erupted and there was a bevy of de-motivational posters.

Well, a confluence of events have brought together my first foray into motivational posters. A few days ago I mentioned that my wife could be the poster child for high capacity magazines. Then, the other night my wife read an article about how Sarah Palin continues to be vilified as the devil, even though she didn't win (who would have thought that the Alaskan Governor was so important). She said she wished we had a hockey stick so she could take a photo of herself with a hockey stick and a gun to show she's like Sarah too. I informed her we did in fact have a hockey stick.


Her eyes lit up! (My wife has is a closet gun nut, she just didn't know it until she met me.) And then a thought came to my mind. "You could wear your tiara too!" Yes, my wife was a pageant girl in her teens and early twenties. Tiaras, Hockey, Firearms. Plus my wife is really hot too! So on the evening of July 3rd, after the kids were in bed, we broke out the firearms and camera. My wife got herself all prepared, hair - check, makeup - check, patriotic outfit - check. Then it was my turn as the photographer to make some magic (I'll have you know that while my wife did some modeling before, I have never claimed to be a photographer - except for the time in college when I did party pics at the sorority parties).


We had a good time, and then I whipped together a few Motivational Posters based on the pictures that we took. Feel free to copy or link to them for any non-commercial use - just provide a citation of where you got it and even a link back to this blog. If for some strange reason you have a commercial venture you would like to use any of these for and wish to pay us money, email me and we can make arangements (I have high quality scans of these images, and if that isn't satisfactory, then I could probably convince my wife to model again!).

Playgrounds

What I really would like is a playground for adults. I took my kids to the mall yesterday and while they were playing on the playland stuff, I had some thoughts.

First, boy do they have it easy. All of the equipment was foam padded and antibacterial (the signs even proclaimed it. The floor had some sort of shock absorbing material under it so that if somebody decided to jump off of the highest toy, they wouldn't get hurt at all. Not only that, all of the shapes were cool: books stacked to make a slide, a pile of fruit with a slide, an ambulance with a tunnel through the back wheels and a slide.

Contrast this to when I was growing up. At my elementary school, the playground was covered with about a foot of pea sized gravel. When you fell off of something you were going to draw blood. The equipment was all metal and wood. Not only that, all of the bolting materials weren't covered up, so if you snagged one, you were drawing blood. Coming out to recess on a sunny day could give you a burn if you were wearing shorts and decided to go down the slide. Then there was the 20 ft poles that you could climb (which we routinely climbed and then jumped off, guess what, kids drew blood this way too). Basically, the school playground was designed to maim and injure, yet somehow, we all survived. (I remember seeing plenty of blood, but no deaths).

We have made much in the way of technological advances since then. Gravel has been replaced by wood chips, which was replaced by ground up tires. Equipment when from bare metal and wood, to plastic coated, to plastic extrusions, to foam filled plastic with anti-bacterial stuff embedded in it. We do our darnedest to make our kids save and they find ways to foil us (read the post about my daughter's fingernail).

Second, while sitting there, I was reminded of some late nights in college when several of my friends would get together and play tag on the playground of one of the apartment complexes. If you were "it" you could go anywhere. If you weren't you couldn't have your feet touching the ground for more than 2 seconds. There were lots of acrobatics going on, and I think in all the times we played only one person sprained their ankle.

As I sat there watching my kids, I couldn't help but think how fun that would be for me if it was scaled up. Think about all of the crazy contortions you might be able to try on some foam jungle gym equipment with a shock absorbent floor! Adults are fun when we revert back and act like kids. It takes away the stress of the real world for a while.