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Class Notes: Human Osteology

Friday: January 6, 2012

Week 12: More Paleopathology

Tuesday:

We checked out a bunch of examples from the Fun Box of Paleopatholgy. This included osteomyelitis, misaligned healed fractures, periosteal reactions, osteophytosis, eburnation, enthesopathy, spondylolisis, osteoarthritis, myositis ossificans, cut marks, ankylosis, and ankylosing spondylosis. Yep, it was one of those days that I wondered why I signed up for a field with such huge words to take notes on.

Thursday:

We had a simple lab day to work on our skeletal projects. I don’t recall where I last left off with my posting on this. Originally, I was assigned an infant skelly. Once I finished the baby, I moved on to some commingled remains from our BARFAA project.

Friday:

Friday was a special class because Dr. Wilson from IUPUI came to give us a Transition Analysis lecture/lab. It was the same as the one I sat in during BARFAA but with my class being smaller and more intimate, I felt like I learned more – of course, that may simply be because this was the second time hearing it. Basically, this new method is advocated to be more reliable, replicable, and quantifiable than past methods of scoring data. If I felt qualified enough to delve into detail, I would. Instead, I will cover just the very basic concepts used.

The traditional methods of scoring the auricular surface and pubic symphysis are sometimes called Suchey-Brooks or the Lovejoy methods. Cranial sutures are also scored for aging. Research has shown, however, that these methods tend to provide results which mimic the original reference sample – making the life tables for all kinds of populations look oddly familiar. These methods utilized phases of bone formation and degeneration. Transition analysis introduces using stages instead. Rather than trying to lump all the evidence given by the feature being studied, it measures each variable independently and provides probability statistics based accordingly, unlike the pigeon-hole phenomenon with a phase-based system. The stage system allows for more variability in the measurements because more possible combinations can be recorded (instead of scoring a single general phase for the development of the apex, ventral rampart, surface porosity and whatnot, it allows individual scores for each of these).

Functionally, transition analysis software lets you input each of these individuals independently, then scores the total age range for the given parts in a bell curve for each feature. The program calculated the P value and gives you the most likely age at death. Its best advantage is omitting that 50+ category. The old idea that people in the past didn’t live as long as we do today is not nearly as accurate as the stories tell. It is simply that most of the methods available for calculating age are unable to distinguish ages among older people. Transition analysis, however, can give you much more precise ages, and the P value still allows a check on accuracy. If you ever get a chance to attend a program on transition analysis, I urge you to check it out.

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One remark!

  1. Now you lost me. Can’t pronounce – spell nor remember those words However, I did understand a little of what you were talking about.
    Keep going Just Maybe I will catch up!

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