year period, sentencing hundreds of defendants to lengthy prison terms. In Texas, a pathologist
faked autopsy results, resulting in as many as 20 death penalty verdicts. A police chemist
elsewhere falsified reports and sent hundreds of innocent people away to jail on rape charges.
Most misuse of scientific evidence is pro-prosecution.
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It is likely that many factors are at work here –
an adversarial system that
indorses and rewards partisanship, professional advancement through forensic
success, laziness, bribery, socialisation or a mindset or a circumstance that
bends a person towards one side of a case (prosecution, plaintiff or defence),
social pressure, blackmail, stress, carelessness, inadequate training, and
inadequate resources.
There are also some specific practices. Lawyers will shop around in a pool of
experts for the right expert opinion (the one who gives evidence favourable to
their case). The willing expert who wants the fee is a gun for hire. They will
write the opinion according to the needs of the lawyers who hire them, even
without a word being spoken. And even without a base desire for the fee there
can be unconscious bias. Moreover, there is typically a large disparity in
resources between the prosecution and most defendants that severely inhibits a
defendant’s ability to challenge unreliable prosecution expert testimony.
Problems in Principle
The notion of the accuracy of scientific evidence rests on a number of
assumptions based on examination of the relevant material. Any time that these
assumptions are not met the resulting conclusion is to that extent equivocal.
Some examples are as follows:
(1)
It is assumed that the material that has been subjected to scientific
analysis is the right material (for example, it is actual material from the crime
scene).
(2)
It assumes that the material is in its original state, or if it is not, that
science has an adequate means for making appropriate allowances.
(3)
It assumes that the finding, for example that Y was caused by X, is
scientifically valid, whereas there may in fact be other possible causes of Y.
(4)
It assumes that the equipment utilised is working properly.
(5)
It assumes that testing procedure possesses perfect certainty. In fact,
some testing merely gives a statistical probability or plausibility. Even if this
evidence of plausibility can be utilised, it assumes that correct statistical
techniques and reasoning have been deployed. Correct statistical procedures
include requirements such as samples not being biased and key results not
being based on outliers.
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Dr. Tom O'Connor faculty.ncwc.edu/toconnor/425/425lect02.htm
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