Believe it or not he’s actually a well respected statistician who was (partially - he does like to over exagerarte his role in this) responsible for getting Lucia de Berk’s conviction over turned. She was a nurse who was convicted of similar crimes to Lucy Letby. He also got another Italian nurse who had been accused of murdering her patients exonerated too, and has since developed a bit of a weird obsession with LL, if she’s convicted, he wants to be the one to do her appeal and get her off.
Thank you that’s interesting. I didn’t realise there was an Italian nurse too.
Fame, they say, can be addictive. And statisticians who are “respected” in their fields (or indeed any other experts) are not immune to that.
I imagine his success in overturning Lucia de Berk’s conviction, and the Italian nurse’s, has given him a taste for a different kind of success and a different kind of fame to the one he’d previously been used to within the confines of his limited audience in the ivory tower that we call academia. No doubt this got to his head and by the sounds of it did weird things to it. Little wonder he’s jumped on the LL case in hope of replicating a similar success and experiencing a similar high that comes from it. The trouble for Richard Gill is that:
1. He’s forgotten the basic assumptions of his own field of expertise: that statistics itself is based on probability, so when he says he can definitively “prove” this or that, this just makes me laugh because what he should really have said is that “based on my statistical model, and the data that I applied that model to, there’s an ‘X’% probability/chance that this is true/false.” But he treats it as gospel, which makes me wonder why he would do or say that. Is he really as bright as we’re told he is? If so, why does he hide the fact that there’s no certainty in statistics?
2. Unlike the de Berk case, the prosecution in LL’s case was careful not to put the weight of its argument on statistics — they relied heavily on medical evidence and witness evidence instead, which is probably why BM didn’t call Richard Gill in as a witness (that, and possibly the fact that he’s made so many unhinged comments on Twitter that one wonders whether bringing him in will actually help the defence or make matters even worse).
3. The insulin cases. Why won’t Richard Gill tell us what the probability is of NICU babies in the U.K. getting poisoned in this way (let alone, get poisoned “accidentally” in this manner)? I’d be very interested in hearing how often, from the point of view of statistics, does this sort of thing happen to babies in NICU. Probably not often at all. So even if we use his own argument, it backfires on him.
I’m sorry I can’t take the likes of Gill too seriously. I’ve seen some academics in my time (people who are bright and successful within the confines of the ivory tower) let fame and success get to their heads. They are used to being surrounded and adored by throngs of fans (colleagues, PhD students, fellow academics from across the globe) looking up to them, complimenting them, begging to work with them, and massaging their ego. They get invited left right and centre to give talks, write papers, publish books etc. And let me make this very clear — whilst the vast majority of academics cope with this sort of attention admirably and professionally — some, a very small minority, from what I’ve seen, sadly, crack under the pressure of the limelight. I suspect that Gill is one of those who’s in the minority: fame seems to have just got to his head.
I don’t know him personally, so I’m just guessing based on his bizarre rants on Twitter. I believe that he may have mistaken being a successful academic statistician with being a detective. He may be an expert in one, but he’s certainly not in the other.
If you’ve read this far (on a Saturday morning of all times) thanks for hearing me out and apologies for the long reply.