FOI Indicates Flawed Data in Initial Shroud Studies

There has been, in the past, controversy over the legitimacy of the data from the Shroud investigation.  This is really no surprise, as there had been a fire in the middle ages and a reweaving of some of the material so naturally, wherever the sample was taken from, is going to affect the end result.

As a quote from the article states:  “The subsequent examination of the data by the Franco/Italian team found evidence, now published in Oxford University’s Archaeometry, which suggests that the methods employed by the 1988 scientists were flawed.”

The original article is here, click here to read it.

There is an acronym in the computer world called GIGO.  GIGO means Garbage In, Garbage Out.  Perhaps there should be a new acronym named TITO, Truth In, Truth Out.  If the original samples are taken from the original cloth, and not repairs, it will bring more truthful results instead of skewed results.

This is the problem in today’s world with surveys, tests, and scientific data.  If a scientist is determined to disprove something, all that is needed is to take the wrong sample to get the wrong result.

Too often in today’s world, whether in science or politics, the original sample is gamed to create a certain result.  On that note, I was in a potential jury pool once.  Both attorneys could ask questions of the potential jury members.  Out of a large room of people there were not able to find 12 people that suited them.  Apparently, they were fishing for people who would bring the verdict they wanted.  They were not able to find their jury that day, but that’s a lot like this problem with the Shroud.

Scientists who don’t want to believe in Jesus don’t want evidence that proves them wrong.  So they take a faulty sample and examine that instead.

What was flawed was that there had been a fire in the Middle Ages. The Shroud had been damaged and repaired. So samples were taken from the Middle Ages repair job and thus dated back to that time. Of course, that was flawed data!

If you like this blog, please link to it or share the link with others. Thank you.

Continue Reading