New solution… the “after top 100″ playlist.

Basically it’s the same structure as the Top 100 (playcount > 0 and selected by most often played), but you add the exclusion of the Top 100 playlist.  I increased the item number to 250 to give it more variety.  Over time, listening to this list will eventually shift the songs up into the Top 100, bringing some of those songs down.  Alternating the two lists should keep the groups near each other play count-wise.  Might need a third tier playlist also, with exclusions of the two previous playlists eventually.

In summation:
I admitted 169 animals to the hospital: 91 dogs, 65 cats, and 13 exotics.
I saw 483 animals as outpatients: 327 dogs, 149 cats, and 7 exotics.
I euthanized 96 animals: 39 dogs, 50 cats, and 7 exotics.

Totals by species: 457 dogs, 264 cats, 27 exotics.
Total: 748 cases.

(These numbers do not include any cases that I saw in conjunction with a specialist (surgeon, cardiologist, oncologist). They represent only cases that I saw alone.)

Now in reflection on these numbers….

• Dogs dogs dogs! There were twice as many dogs as cats – thank god. Dogs are muzzle-able. Cats have claws and infection-causing pointy teeth.
• Cats are sicker when they finally get to the vet. I’m sure I’ve mentioned this before but New Yorkers will bring their dog to the vet after one weird poop, but the cat can hide in the closet for two weeks before they do anything about it.
• It feels like I euthanized way more than 96 animals. On New Year’s Day alone I swear I euthanized at least ten animals. (“Just make it through the holidays…”)
• Numerically the total is not very impressive. A general practitioner who works 260 days a year would probably see roughly twice to three times as many appointments. I worked 330 days in the last year and saw only 748. These numbers do not represent, however, any of the inpatient care. For at least 18 weeks of the year I was on a team managing 10+ inpatients. For another 18 weeks at least 4-5 inpatients. And 1-2 for the remaining weeks.
• Anyway you look at it – it was a lot of work.

It’s always been my opinion that, in the social sciences at least, most connections that are drawn between conditions are plagued with confounding.

Take the graph above – from the National Center on Addiction and Substance Abuse at Columbia University report released yesterday: Wasting the Best and the Brightest: Substance Abuse at America’s Colleges and Universities. Doesn’t it seem likely that those individuals who are more likely to join Greek houses are also going to be, relative to the average student, potentially more social? After all, joining a Greek house is an active choice made by that student. And realistically, isn’t drinking a part of being social in college? Those are clearly summary statements, but I’m just speaking in averages.

I’m not condoning binge drinking, and I do believe that the group mentality that Greek systems foster can lead to absolutely inappropriate behavior, but I just don’t like statistics that seem plagued with confounding.

Confounding comes up everywhere you look. Once you’re aware of the concept it seems easy enough to poke holes in every argument. Next time you hear someone propose an inappropriate summary connection, ask them if they’ve considered all the confounding variables. Likely they’ll look confounded.