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have attempted to relate aspects of the age-at-death structure to the presence of the Black
Death (bubonic plague) while Redfern and DeWitte (2011) have examined the effect of
“Romanization” on age-at-death structures. Although the analyses become increasingly
more difficult as one pushes further back in time, there is now research and lively debate
over the origins of modern human mortality based on data from Australopithecines
through modern humans ( Caspari and Lee, 2004, 2006 ; Hawkes and McConnell, 2005 ;
Minichillo, 2005 ). Bocquet-Appel and Arsuaga (1999) have presented evidence that two
important Neandertal skeletal samples represent mortality from catastrophes rather
than from ordinary accretional deaths. Such findings are important, because they alter
our views about the representational nature of skeletal assemblages. On a more recent
scale, Bocquet-Appel (2002) and Bocquet-Appel and Naji (2006) have examined the demo-
graphic transition that occurred with the Neolithic transition. All these studies demon-
strate the need for, and benefit of,
integrating demographic analyses into skeletal
biology research.
WHAT ROLE CAN SEX RATIOS AND AGE-AT-DEATH STRUCTURES
PLAY IN FORENSIC ANTHROPOLOGY?
This chapter has primarily focused on paleodemography, and as such we have had
nothing yet to say about the role of sex ratios and age-at-death structure in forensic anthro-
pology. On the surface, it would not appear that demography plays any particular role in
forensic anthropology. Why would we want to estimate the sex ratio and/or the age-at-death
structure in a forensic setting? In fact, demographic analysis can be vitally important in the
forensic setting. To look at the role that demography can play in forensic anthropology we
need to consider two different settings. Konigsberg and colleagues ( Konigsberg et al.,
2006, 2008, 2009; Steadman et al., 2006 ) have referred to these two different settings as
a problem in estimation versus a problem in building evidence for identification of an indi-
vidual. We begin with a brief discussion of the estimation problem and then turn to a discus-
sion of the evidentiary problem.
The estimation problem is the one that traditionally was handled by an osteologist who
would build a biological description that might aid in the eventual identification of the indi-
vidual from a missing persons list. Where the demographic analysis is concerned, the oste-
ologist would estimate the age-at-death and sex from the remains. But here we need to be
careful to separate the acts of observing, scoring, and possibly measuring the bones and
teeth from the actual act of estimating the age-at-death and sex of the remains. Steadman
and Konigsberg (2009) discuss “the problem of bias” that can arise if an osteologist enters
into their analysis with prior knowledge about the case. If the osteologist has been told by
law enforcement “we think these are the bones of a particular missing person who was
34 years old,” then this can no doubt influence the osteologist. So the osteologist must
make their basic observations blind to any possible identification. But once an osteologist
has made their basic observations then the context of the case becomes very important.
Note that the use of Bayes' theorem (such as in Equations 11.5, 11.11, and 11.20 ) required
prior demographic information, and this prior information must come from the context
of the case.
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