The post-it note

Is Lucy’s post-it note a confession? Whether you will see it as a confession or a cry of innocent anguish depends on whether *you* have a heart and a brain. If you read it carefully, you will see that Lucy does not say that she killed those babies. She says that *they said* she killed those babies. Yes, she does say she is evil. She thinks she is clearly a bad nurse who apparently couldn’t save those babies, despite her (possibly too energetic, and certainly not well supervised) attempts. More seriously, she had had an affair with an older married man, a doctor, who later dumped her and betrayed her. She spoke out about doctors’ mistakes and about the catastrophic hygienic circumstances in which she and her colleagues had to work. For two years, doctors had tried to have her taken off that ward, because she pissed them off. Her colleague nurses loved her for her forthrightness and lovely character. She is so sorry for the suffering she caused her parents and step-brothers. She is considering suicide. She has PTSD.

This deciphering of the note was created by https://x.com/chrisjclarkesq?s=21&t=1S47Jut6K2dqjKzr1sc-4A , known as Mycroft on ‘X’, that is the ‘X’ formerly known as Twitter.

Contempt of court

“Contempt of court” means disrespect of a court. Now, it is certainly true that I am disrespectful of the court which convicted Lucy Letby. I think that the trial was unfair and that the judge did not understand what was going on. Nor did the jury. The jury was incomplete and the verdicts were not unanimous, yet the sentence was the heaviest possible. The defence made little attempt to defend their client and the UK tabloid newspapers had convicted Lucy long ago. On one of the days that she was arrested, the TV vans were in her street, before the police arrived to knock on her door and take her away. Six years of police investigation by a team of 60 to 70 police inspectors, including a large PR department (read: a little troll farm), did not find any conclusive proof of any wrongdoing by Lucy Letby at all. Yet already Cheshire Constabulary have signed a contract with Netflix and ITN for a documentary on their fantastic work nailing the UK’s most horrific female serial killer ever.

Now, “contempt of court” is also a very serious criminal offence in the UK, but as such, it has a very narrow definition. The definition involves the motive of the perpetrator. This is like killing someone. Killing a person might be murder. But it might be an accident. It might be caused by negligence. It is only premeditated murder if the person who killed the victim planned to do so in advance and deliberately and successfully carried out their plan. Lucy Letby is convicted of a large number of premeditated murders and murder attempts. The jury believed that she had motive and opportunity and deliberately tried in some cases numerous times to kill the same infant.

As the trial of Lucy Letby proceeded, various independent observers with a scientific background started studying the case and commenting on it on various internet sites. There was my own blog, gill1109.com. There was Peter Elston’s “Chimpinvestor” blog, chimpinvestor.com. There was Scott McLachlan’s Law, Health and Technology “Substack”. There was Sarrita Adams elaborate and dedicated website rexvlucyletby2023.com, later morphed into the even more elaborate ScienceOnTrial.com. Numerous individuals of course also tweeted on the case, several FaceBook groups started up, several SubReddits were founded. Cheshire Constabulary kept a close eye on social media and dedicated websites and became more and more active in trying to suppress any support of the defence of Lucy Letby, though all those Twitter users calling for the return of hanging and for Lucy to be assassinated as soon as possible in the most horrific way, were presumably encouraged by Cheshire Constabulary.

Around May, while the trial still had a few months to run, the police apparently started to become nervous. Threatening emails were sent to myself, Peter Elston, and to Sarrita Adams, telling us that our websites must be taken down and links to those sites on social media should be removed. We know that the police also attempted to find out who was behind the Law, Health and Technology substack, but did not succeed so easily.

Of course, they found me, easily. But how did they discover the identity of the anonymous owner of rexvlucyletby2023.com, Sarrita Adams, who tried very hard indeed, for very sound personal reasons, to remain anonymous? The answer is simple: at some point Sarrita and I emailed to the court trying to alert the judge that the trial was unfair, and that important scientific evidence was hidden from the jury and the public. We did this through emails to the clerks of the court, asking them to bring our messages to the attention of the judge. However, this is not what they did. They gave the messages to police inspectors from Cheshire Constabulary, who were in court every day, hobnobbing with both the barristers, the judge, and with top NHS lawyers.

They also divulged the identity of Sarrita Adams to their internet trolls who rapidly managed to dig up a lot of dirt about Sarrita and dox her on Twitter.

The email letters which Peter, Sarrita and I were sent, are very interesting. They say that our internet activities were discovered by the police and that the police had discussed with the defence team, the defendant, and the judge, and that the judge said that what we were doing appeared to be contempt of court. We should remove our websites and remove all links to them on social media. According to the police, Sarrita and I were “associates” though we were in no way associated at all except in our common belief that the trial was unfair and the scientific evidence incorrectly interpreted. Yes, we had communicated with one another. The judge did point out that this was just his initial reaction and he couldn’t state that it was contempt of court without hearing our motivation from us. This shows again that he never received our emails to the court. Our stated motivation was to prevent a possible miscarriage of justice, not to cause a miscarriage of justice by subversion of the jury. We were attempting to contact all relevant authorities, not the jury at all. Indeed, since later the jury found Lucy guilty of the most heinous crimes, it is clear that we did not influence the jury at all.

I replied to the police by email that I would do what they asked. I did not remove my blog posts on the case but I did diligently delete links to Sarrita’s site and all tweets by myself with links to my blog or Sarrita’s website. I did not get a reply, though I asked who was emailing me and said that I wanted to talk to them, by telephone or Zoom. The letters had no phone number and no first name of whoever wrote them. I called Cheshire Constabulary by phone but they couldn’t help me because I did not know the initials or first name of whoever had emailed me.

About three weeks later, the jury was now deliberating in private. One Friday evening very late I was shocked by a knock at the door. (Actually, I had already gone to bed, but my son was visiting and woke me up. Thankfully, my wife slept through the whole thing). Local Dutch police wanted to deliver two letters to me, on paper, in person. They had been instructed to verify my identity and naturally, I did show them my Dutch passport. The letters were almost identical to the email letters which I had received earlier, and had already and immediately replied to. They did not have wet signatures, they were clearly printooouts of pdfs. Similar, but not identical to what I had already received.

So now Cheshire Constabulary had legal proof, with the help of their Dutch colleagues. that I had indeed received their letters! The letters threatened arrest next time I tried to enter the UK, and noted that contempt of court carries a two year prison sentence and a huge fine – namely, the costs of rerunning the whole trial with a fresh jury. It was pointed out that as a UK citizen I was still subject to UK law even though I lived in another country. The same thing was said to Sarrita, who lives in California, but is also a British citizen.

This was clearly intended to intimidate, and indeed it was very intimidating. I will now reproduce the original email letters and the later, paper, version. The wording is fascinating, the intention was to intimidate, but UK police cannot charge me with contempt of court without an order from a magistrate, and as Judge Goss remarked, he would need to know my actual motives before he could say that I had indeed likely committed the crime of contempt of court.

How to lie with data

This spreadsheet was shown on TV both yesterday (Friday August 18, the day of the verdicts) and at the start of the trial of Lucy Letby. Apparently, Cheshire Constabulary find this absolutely damning evidence against Lucy. And indeed, many journalists seem to agree.

The 25 events are almost all of the events at which LL was present during the periods investigated. They are suspicious because she was under suspicion when the police started their investigations. Not surprisingly, most nurses are not present at many of these events. And of course, many nurses probably work far fewer hours than LL. Many are often on administrative duties.

The doctors on the ward are of course missing. Doctors were never investigated as suspects but from the start of police investigations apparently always believed to speak gospel truth. During cross-examination, during the trial, some of them have changed various parts of their stories. Of course, unlike Lucy, they do not lie, since they could never (under oath in court, or earlier, when being interviewed as witnesses by police) be saying untruths in order to deceive.

Back to the spreadsheet. When drawing conclusions from any data it is important to know how it was gathered. It is important to know what data is missing, but would be needed draw even the most preliminary and tentative inferences.

There was an NHS investigation into the raised rates of deaths and collapses at Countess of Chester Hospital (CoCH) in summer 2015 and summer 2016. It was published in 2017 by the Royal College of Paediatrics and Child Health (RCPCH). The investigation blamed the consultants for the appalling low standard of care, and the terrible situation regarding hygiene. The RCPCH investigators actually wrote that nurse Lucy Letby could not be associated with the events, but that passage was redacted out of the published report for privacy reasons. We know that already, consultants had presented their fears to hospital management. One of them (successful TV doctor and FaceBook influencer dr Ravi Jayaram) was on TV yesterday proudly telling the world that he had been vindicated. Management was inclined not to believe them, and did not act on them, but they certainly came to the ears of the RCPCH. On publication of the report, four consultants had had enough, and went to the police with their suspicions that LL was a murderer.

Thanks to FOI requests and statistical analysis by independent scientists, we now know that the rate of events (deaths and collapses) is just as much raised when Lucy is not on the ward as it is when she is on the ward. A lot of medical information (as well as the state of the drains at CoCH) points to a seasonal virus epidemic.

The elevated rate went back to normal after the hospital was down-graded (no longer accepting high risk patients), and when the drains were rebuilt, and when the senior consultant retired, all of which happened soon after the police investigation started. Incidentally, the rate of still-births and miscarriages show exactly the same pattern.

Lucy must certainly have been a witch in order to kill babies in the womb and even when she is far from the hospital.

Those familiar with miscarriages of justice involving serial killer nurses will be familiar with this police and prosecution tactic. Is it evil or is it just stupid? (cf. Hanlon’s razor). I think it is quite simply “learnt”. Police and prosecution learn what convinces jurors over the years, and that is why the same “mistakes” are made again and again. They work!

The Lucy Letby case

Note: [20 August 2023] This post is incomplete. It needs a prequel: the history of medical investigations into two “unexplained clusters” of deaths at the neonatal ward of the Countess of Chester Hospital. It needs many sequels: statistical evidence; how the cases were selected (the Texas sharpshooter paradox) and the origin of suspicions that a particular nurse might be a serial killer; the post-it note; the alleged insulin poisonings; the trouble with sewage backflow and the evidence of the plumber; the euthanasias. For the medical material, the site to visit is the magnificent https://rexvlucyletby2023.com/.

Lucy Letby, a young nurse, has been tried at Manchester Crown Court for 7 murders and 15 murder attempts on 17 newborn children in the neonatal ward at Countess of Chester Hospital, Chester, UK, in 2015 and 2016.

She was found:– Guilty of 7 counts of murder (against 7 babies)
– Guilty of 7 counts of attempted murder (against 6 babies)
– Not guilty on 2 counts of attempted murder (against 2 of the 6 babies she *was* found guilty of attempting to murder). No decision was reached on 6 counts of attempted murder against 6 different babies. However, 2 of those 6 she was also found guilty of a different count of attempted murder. [Thanks to the commenter who corrected my numbers.]

The prosecution dropped one further murder charge just before the trial started, on the instruction of the judge. Several groups of alleged murders and murder attempts concern the same child, or twin or triplet siblings. All but one child was born pre-term. Several of them, extremely pre-term.

I’m not saying that I know that Lucy Letby is innocent. As a scientist, I am saying that this case is a major miscarriage of justice. Lucy did not have a fair trial. The similarities with the famous case of Lucia de Berk in the Netherlands are deeply disturbing.

The image below summarizes findings concerning the medical evidence. This was not my research. The graphic was given to me by a person who wishes to remain anonymous, in order to disseminate the research now fully documented on https://rexvlucyletby2023.com/, whose author and owner wishes to remain anonymous. Note that the defence has not called any expert witnesses at all (except for one person: the plumber). Possibly, they had not enough funds for this. Crowd-sourcing might be a smart way of getting the necessary work done for free, to be used at a subsequent appeal. That’s a dangerous tactic, and it seems to me that the defence has already taken a foolish step: they admitted that two babies received unauthorised doses of insulin, and their client was obliged to believe that too.

This blog post started in May 2023 as a first attempt by myself to blog about a case which I have been following for a long time. The information I report here was uncovered by others and is discussed on various internet fora. Links and sources are given below, some lead to yet more excellent sources. Everything here was communicated to the defence, but they declined to use it in court. Maybe they felt their hands were bound by pre-trial agreement between the trial parties as to what evidence would be brought to the attention of the jury, which witnesses, etc.

An extraordinary feature of UK criminal prosecution law is that if exculpatory evidence is in the possession of the defence, but not used in court, then it should not be used at a subsequent appeal, whether by the same defence team or a new one. This might explain why the defence team would not even inform their client of their knowledge of the existence of evidence which exonerated her. Even though, it is also against the law that they did not, as far as we know, disclose evidence which they had which was in her favour. The UK law on criminal court procedure is case law. New judges can always decide to depart from past judges’ rulings.

A very important issue is that the rules of use of expert evidence is that all expert evidence must be introduced before the trial starts. It is strictly forbidden to introduce new expert evidence once the trial is underway.

UK criminal trials are tightly scripted theatre. The jury is of course incommunicado, very close to its verdict, and I do not aim to influence the jury or their verdict. I aim to stimulate discussion of the case in advance of a likely appeal against a likely guilty verdict. I wish to support that small part of the UK population who are deeply concerned that this trial is going to end in an unjustified guilty verdict. Probably it will, but that will not be the end. So much information has come out in the 9 months of the trial so far, that a serious fight on behalf of Lucy Letby is now possible. Public opinion crystallised long ago against Lucy. It can be made fluid again, and maybe it can even be reversed, and this is what must happen if she is to get a fair re-trial.

As a concerned scientist who perceives a miscarriage of justice in the making, I attempted to communicate information not only to the defence but also to the prosecution, to the judge (via the clerk of the court), and to the Director of Public Prosecutions. That was a Kafkaesque experience which I will write about on another occasion. Personally, I tend to think that Lucy is innocent. That was however not my reason for attempting to contact the authorities. As a scientist, it was manifestly clear to me that she was not getting a fair trial. Science was being abused. I tried to communicate with the appropriate authorities. I failed to get any response. Therefore I had to “go public”.

Here is a short list of key medical/scientific issues, originally copied from an early version of the incredible and amazing website https://rexvlucyletby2023.com/, with occasional slight rephrasing and some small, hopefully correct, additions by myself. That site presents full scientific documentation and argumentation for all of the claims made there.

  1. Air embolism cannot be determined by imaging, and can only be determined soon after death, and requires the extraction of air from the circulatory system, and analysis of the composition of the air using gas chromatography.
  2. The coroner found a cause of death in 5 out of 7 of the alleged murder cases. Two of them appeared to be, in part, related to aggressive CPR, two appeared to be due to undiagnosed hypoxic-ischemic encephalopathy and myocarditis, one of the infants received no autopsy, and the other infant was determined to have died due to prematurity. It is highly unusual for the cause of death to be altered years after the fact and using methodology that is not supported by the coroner’s office.
  3. The two claims of insulin poisoning are not supported by the testing conducted, and the infants (who are still alive and well) did not have dangerously low or dangerously high blood glucose levels for any period of time. There are many physiological reasons that could explain their low blood glucose during the whole period. In one of the two cases, assumptions are being made on the basis of one test taken at a single time point, clearly inconsistent with the other medical readings, and contravening the manufacturer’s own instructions for use (see image below). The report detailing the conclusions from that single test violates the code of practice of the forensic science regulator. Moreover, it appears that some numerical error has been made in the necessary calculation, resulting in an outcome which is physiologically impossible (or the person responsible did not know about the so-called “hook effect”). The mismatch between C-peptide and insulin concentration does not prove that the excess insulin found must have been synthetic insulin. There are many other biological explanations for a mismatch. No testing was done to determine the origin of the insulin. Similarly, there are many innocent explanations for the detection of some insulin in a feeding bag.
  4. The air embolism hypothesis is confusing because it fails to explain why some children apparently perished and others did not, and it has not been supported by the minimal necessary measurements.
  5. In at least one case, Lucy is blamed with causing white matter brain injury. This claim is utterly dishonest. The infant who experienced this brain injury was born at 23 weeks gestation, and white matter brain injury is associated with such early births. Further, there is sufficient evidence that demonstrates that enterovirus and parechovirus infection has been linked to white matter brain injury in neonates, resulting in cerebral palsy.
  6. At the time of the collapses and deaths of the infants, enterovirus and parechovirus had been reported in other hospitals. There is a history of outbreaks of these viruses in neonatal wards in hospitals around the world. They especially harm preterm infants who do not yet have a functioning immune system. It is reported that many parents of the infants were concerned that their ward had a virus (as was Lucy) and that Dr Gibbs denied this was so. To date we have seen no evidence to show they did any viral testing, and if they did what the results were.

Then a fact pertaining to my own scientific competence.

Both prosecution and defence were warned long ago about the statistical issues in such cases. Both have responded that they are not going to use any statistics. They are also not using the services of any statistician. Seems the RSS report https://rss.org.uk/news-publication/news-publications/2022/section-group-reports/rss-publishes-report-on-dealing-with-uncertainty-i/ has had the opposite effect to that intended. Amusingly, the same thing happened in the case of Lucia de Berk. At the appeal the prosecution stopped using statistics. She was convicted solely on the grounds of “irrefutable medical scientific evidence”. (Here, I’m quoting from the words both spoken by the judges and written down on the first page of their > 100 page report of the reasons and reasoning which had led to their unshakable conviction that Lucia de Berk was guilty. The longest judge’s summing up in Dutch legal history). I was one of the five coauthors of the RSS report. We were a “task force”, formally commissioned by the “Statistics and the Law” section of the society. I consider it the most important scientific work of my career. It took us two years to put together. We started the work in 2020; we had seen the Lucy Letby trial on the horizon since 2017 when police investigations started and the suspect being investigated was already common knowledge.

The UK does not have anything like that because a jury of ordinary folk are the ones who (legally) determine guilt or innocence. This is a clever device which makes fighting a conviction very difficult; no one can know what arguments the jury had in their mind, no one knows what, if anything, was the key fact that convinced them of guilt. Ordinary people are convinced by what seems to be a smoking gun, they then see all the other evidence through a filter. This is called “confirmation bias”. In the Lucy Letby case, the smoking gun was probably the post-it note, and the insulin then seems to clinch the matter. The prosecution cross-examination convinces those who already believe Lucy is guilty that she moreover is constantly lying. More on all this in later posts, I hope.

Back to the insulin. Here are the instructions on the insulin testing kit used for the trial, taken from this website http://pathlabs.rlbuht.nhs.uk/ccfram.htm, the actual file is http://pathlabs.rlbuht.nhs.uk/insulin.pdf. Notice the warning printed in red. Yes, it was printed in red, that was not something I changed later. (All this is not my discovery; the person who uncovered these facts wishes to remain anonymous).

The toxicological evidence used in the trial violates the code of practice of the UK’s Forensic Science Regulator (see link below). It should have been deemed inadmissible. Instead, the defence has not disputed it, and thereby obliged their own client Lucy to agree that there must have been a killer on the ward. The jury are instructed to believe that two babies were given insulin without authorization, endangering their lives. (The two babies in question are still very much alive, to this day. Probably now at primary school.)

The defence stated to me that they cannot inform Lucy of the alternative analysis of the insulin question. It appears to me that this violates their own code of practice. Do they feel bound by the weird rules of UK’s criminal prosecution practice? Their client, Lucy Letby, is herself essentially merely a piece of evidence, seized by the police from what they believe is a scene of crime. No one may tamper with it during the duration of her own trial, which is lasting 10 months! I think this constitutes an appalling violation of basic human rights. The UK laws on contempt of court are meant to guarantee a fair trial. But in the case of a 10-month trial on 22 charges of murder and attempted murder, they are guaranteeing an unfair trial.

Lucy’s solicitor refused to pass on a friendly personal letter of support to Lucy or to her parents because she had not instructed him to do so. Should one laugh or cry about that excuse? I have the impression that he is not very bright and that he may have been convinced she is guilty. If so, I hope he is changing his mind. In the UK, the solicitor does all the legwork and communication between the client and the defence team. The barrister does the cross-examinations and the court theatrics, but probably never builds up a personal relationship with his client. Lucy has been all this time prison, in pre-trial detention, far from Manchester or Hereford. This might explain the extraordinarily weak defence which has been put up so far. But it might be deliberate.

One must take into account the fact that funding for legal support is meagre. The prosecution has been working on the case for 6 or so years, with unlimited resources. The defence has had a relatively very short time, with very limited resources. Probably the solicitor and the barrister already put in many more hours than they are paid for. There are no funds for expensive scientific witnesses. It is very possible that the defence team well understands that they cannot put up a serious defence during the 9 to 10 months of the trial, but that precisely this time period, with a huge number of revelations being made outside the trial, material for a serious defence during an appeal has been “crowd-sourced”. It seems to me that this mass of high-quality independent scientific work provides plenty of grounds for an appeal, in the case that the jury hands down a guilty verdict.

Some links:

Sarrita Adams’ Science on Trial website

scienceontrial.com

Formerly: https://rexvlucyletby2023.com/


Scott McLachlan’s Law Health and Tech blog

LL Part 0: Scepticism in Action: Reflections on evidence presented in the Lucy Letby trial. https://lawhealthandtech.substack.com/p/scepticism-in-action

LL Part 1: Hospital Wastewater https://lawhealthandtech.substack.com/p/ll-part-1-hospital-wastewater

LL Part 2: An ‘Association’ https://lawhealthandtech.substack.com/p/ll-part-2-an-association

LL Part 3: Death already lived in the NICU Environment, https://lawhealthandtech.substack.com/p/ll-part-3-death-already-lived-in

LL Part 4: Outbreak in a New NICU: Build it and the pathogens will come…https://lawhealthandtech.substack.com/p/ll-part-4-outbreak-in-a-new-nicu

LL Part 5: The Demise of Child A https://lawhealthandtech.substack.com/p/ll-part-5-the-demise-of-child-a

LL Part 6: The Incredible Dr Dewi Evans https://lawhealthandtech.substack.com/p/ll-part-6-the-incredible-dr-dewi

LL Part 7: The Demise of Child C. https://lawhealthandtech.substack.com/p/ll-part-7-the-demise-of-child-c

LL Part 8: The Death of Child D. Had she been left or resumed on CPAP, she might still be alive today. https://lawhealthandtech.substack.com/p/ll-part-8-the-death-of-child-d


Peter Elston’s “Chimpinvestor” blog

Do Statistics Prove Accused Nurse Lucy Letby Innocent? https://www.chimpinvestor.com/post/do-statistics-prove-accused-nurse-lucy-letby-innocent This splendid and comprehensive blog post also has a large list of links to reports and data sets. Yet more data analysis can and should be done. This site gives anyone who wants to a quick-start. And after that, two more outstanding posts…

https://www.chimpinvestor.com/post/more-remarkable-statistics-in-the-lucy-letby-case

https://www.chimpinvestor.com/post/the-travesty-of-the-lucy-letby-verdicts


Data obtained from FOI requests

FOI requests provided some fantastic data sets https://www.whatdotheyknow.com/request/neonatal_deaths_and_fois#incoming-1255362 see especially https://www.whatdotheyknow.com/request/521287/response/1265224/attach/2/FOI%204568×1.xlsx?cookie_passthrough=1


How forensic science should be reported in court

Forensic Science Regulator: statutory code of practice https://www.gov.uk/government/publications/statutory-code-of-practice-for-forensic-science-activities


One of numerous enterovirus and parechovirus epidemics in neonatal wards

Cluster of human parechovirus infections as the predominant cause of sepsis in neonates and infants, Leicester, United Kingdom, 8 May to 2 August 2016 https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2016.21.34.30326


Someone commissioned a pretrial statistical and risk analysis – results not used in the trial

Lucy Letby Trial, Statistical and Risk Analysis Expert Input. Who commissioned this analysis, and what did it yield? (I can give you the answer after the verdict has come out). https://www.oldfieldconsultancy.co.uk/lucy-letby-trial-statistical-and-risk-analysis-expert-input/


The RSS (statistics and law section) report – not used in the trial

Royal Statistical Society: “Healthcare serial killer or coincidence?
Statistical issues in investigation of suspected medical misconduct” by the RSS Statistics and the Law Section, September 2022 https://rss.org.uk/news-publication/news-publications/2022/section-group-reports/rss-publishes-report-on-dealing-with-uncertainty-i/

At a pre-publication meeting of stake-holders held to gain feedback on our report, a senior West Midlands police inspector told me “we are not using statistics because they only make people confused”. Lucy’s sollicitor and barrister knew well in advance of our report, were even given names of excellent UK experts whom they could consult, but did not bother to contact one of them. No statistics in our courts please, we are British! Yet the UK has the best applied statisticians and epidemiologists in the world.


Article in “Science” about my work on serial killer nurses

Unlucky Numbers: Richard Gill is fighting the shoddy statistics that put nurses in prison for serial murder. Science, Vol 379, Issue 6629, 2022. https://www.science.org/content/article/unlucky-numbers-fighting-murder-convictions-rest-shoddy-stats


Two subreddits on the Lucy Letby case

https://www.reddit.com/r/scienceLucyLetby/ (the Lucy Letby Science subreddit)

https://www.reddit.com/r/lucyletby/ (general)


Medical Ethics

John Gibbs, recently retired Consultant Paediatrician at the Countess of Chester
Hospital, defined Medical Ethics as “Playing God with Life and Death decisions.”
See article “Medical Ethics” on page 6 of The Messenger, Monthly Newsletter of St Michael’s, Plas Newton, Chester) – reporting on talk by Dr John Gibbs, retiring paediatrician at CoCH. https://stmichaelschester.com/wp-content/uploads/2019/04/Messenger-April-2020.pdf. Audio: https://stmichaelschester.com/sermons/encounter-medical-ethics/


The state of forensic science in the UK

https://www.bbc.co.uk/sounds/play/m001k7vt?partner=uk.co.bbc&origin=share-mobile “The UK’s forensic science used to be considered the gold standard, but no longer. The risk of miscarriages of justice is growing. And now a new Westminster Commission is trying to find out what went wrong. Joshua talks to its co-chair, leading forensic scientist Dr Angela Gallop CBE, and to criminal defence barrister Katy Thorne KC.”


Criminal Procedure Rules and Criminal Practice Directions

Revised rules came out earlier this year, so maybe they do not apply to a trial which started earlier. Still, they express what the Lord Chief Justice of England and Wales presently wants to promote. https://www.judiciary.uk/guidance-and-resources/message-from-lord-burnett-lord-chief-justice-of-england-and-wales-new-criminal-practice-directions-2023/ . See especially Section 7 of his “Criminal Practice Directions (2023)” https://www.judiciary.uk/wp-content/uploads/2023/04/Criminal-Practice-Directions-2023-1-3.pdf


New expert evidence cannot be admitted once a trial is in progress

“The courts have indicated that they are prepared to refuse leave to the Defence to call expert evidence where they have failed to comply with CrimPR; for example by serving reports late in the proceedings, which raise new issues (Writtle v DPP [2009] EWHC 236). See also: R v Ensor [2010] 1 Cr. App. R.18 and Reed, Reed & Garmson[2009] EWCA Crim. 2698″. This quote comes from https://www.cps.gov.uk/legal-guidance/expert-evidence. Note, a judge is always allowed to break with precedence. The rule is not actually a permanent rule, it is merely a description of current practice. Current practice evolves when and if a new judge sees fit to break with precedence. Obviously, he would have to come up with good legal reasons why he believes he has to do that. It’s his prerogative, his free choice. That’s the essence of case law, aka common law.

Het interview

Interview in “Stentor”, gepubliceerd vorige Zaterdag

Richard Gill heeft met het weerleggen van statistisch bewijs al twee medische seriemoordenaars vrij gekregen, onder wie Lucia de Berk. © Rob Voss

Deze Apeldoornse wetenschapper redt onschuldige zusters uit de gevangenis: De mens wil helaas niet in toeval geloven

Wetenschapper Richard Gill uit Apeldoorn zorgde er mede voor dat Lucia de Berk werd vrijgesproken. Datzelfde kreeg hij voor elkaar bij een vergelijkbare zaak in Italië en nu gaat hij voor de hattrick in Engeland. Wat drijft hem? 

Anne Boer 28-05-22, 08:00

Pure wetenschappelijke nieuwsgierigheid, dat is wat hem drijft, zegt de internationaal vermaarde wiskundige Richard Gill uit Apeldoorn. Als expert op het terrein van statistieken werkte Gill (70) voor het Openbaar Ministerie en het Internationaal Strafhof. Bijna zes jaar is hij gepensioneerd en staat hij te boek als emeritus professor in de statistiek aan de Universiteit Leiden.

Met zijn kennis over het gebruik van statistieken heeft hij vanuit zijn werkkamer de onschuld kunnen aantonen van twee verpleegkundigen die waren veroordeeld voor seriemoorden: de Nederlandse Lucia de Berk en de Italiaanse Daniela Poggiali. Nu zet hij zich in voor de vrijlating van verpleegkundige Ben Geen uit Engeland.

Klinkklare onzin

Alle drie zouden tijdens hun werk patiënten hebben gedood. Lucia de Berk werd zelfs veroordeeld voor zeven moorden. De bewijslast was vooral gebaseerd op statistieken. Als Lucia werkte, zouden er meer patiënten overlijden dan tijdens de diensten van haar collega’s. Het bleek klinkklare onzin, zoals Gill het fijntjes verwoordt. ,,Kwestie van roddel en achterklap, zoeken naar een zondebok om de reputatie van het ziekenhuis te redden en aannames, terwijl er helemaal geen moord is gepleegd.’’

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De mens wil helaas niet in toeval geloven, we willen een oorzaak hebben. Daarom geloven we ook in duivels en goden

Statistisch bewijs speelt een grote rol in onderzoek, ook naar seriemoordenaars in de medische wereld. ,,Maar dan moet je de cijfers wel goed interpreteren’’, vindt Gill. ,,Als er ogenschijnlijk veel mensen overlijden in een ziekenhuis, moet je eerst goed kijken naar de oorzaak. Zijn er misschien meer patiënten dan anders? Zijn ze zieker dan in andere perioden? Is de methode van registreren aangepast? Zijn er wijzigingen in de staf? Als je meteen kijkt welke verpleegkundige aanwezig was, sla je bovendien de belangrijkste vragen over: is er sprake van moord of is het medisch falen of zelfs natuurlijk overlijden?’’

Dat raakt volgens Gill meteen aan een ander pijnlijk punt. ,,Een ziekenhuis is een plek waar mensen doodgaan, maar vaak is de doodsoorzaak niet duidelijk. Dat kan leiden tot clusters van verdachte overlijdens. Je moet wel weten welke doden je telt, anders zoekt de politie bewijs voor beweringen.’’

Gepassioneerd

Volgens Gill moet je altijd in gedachten houden dat er een goede, onschuldige reden kan zijn voor een gebeurtenis. ,,Kijk vooral hoe vaak iemand werkt. Fulltime verpleegkundigen maken meer doden mee dan parttimers. Als iemand fulltime werkt en ook nog gepassioneerd bezig is met haar of zijn vak, is de kans nog groter dat die persoon aanwezig is als iemand overlijdt, dan iemand die een paar dagen per week werkt of strikt de uren werkt die in het rooster staan.”

Wetenschapper Richard Gill. © Rob Voss

Nooit mag je volgens hem een rare samenloop van omstandigheden uitsluiten. ,,Die gebeuren, ook zonder moord. Beroemd is het voorbeeld van een Amerikaans stel dat op één dag in twee verschillende loterijen de hoofdprijs won. Hoe groot is de kans dat zoiets gebeurt? Het gebeurde toch echt. De mens wil helaas niet in toeval geloven, we willen een oorzaak hebben en zoeken een zondebok. Daarom geloven we ook in duivels en goden.’’

Liefde

Richard Gill is geboren in Engeland. Zijn vader was ook wetenschapper. De liefde brengt hem in 1974 op 23-jarige leeftijd naar Nederland. Hij is zes jaar eerder op vakantie als een blok gevallen voor een dochter van een Nederlandse vriend van zijn vader. Beide vaders werken voor Wavin uit Hardenberg. Na wat omzwervingen belandt Gill begin jaren 80 in Apeldoorn, om er nooit meer weg te gaan. Hij woont in een oud herenhuis, in een zee van weelderig groen. Dit was het ouderlijk huis van zijn vrouw. Om financieel het hoofd boven water te houden, werkt hij extra hard om snel carrière te kunnen maken.

De medische wereld komt al vroeg op zijn pad. Na een studie wiskunde in Cambridge promoveert hij op onderzoek naar de vraag hoelang kankerpatiënten bij bepaalde behandeling overleven. Zijn rekenmethode blijkt een uitkomst en wordt inmiddels ook op andere terreinen toegepast. ,,Het kwam toevallig op mijn bord. Ik had geen onderwerp en mijn promotor haalde dit onderwerp uit zijn la. Het heeft veel impact gehad en de methode wordt nog massaal gebruikt.’’

Heksenjacht

Zijn vrouw, die historicus is, wijst hem al in een vroeg stadium op de zaak Lucia de Berk, die later veroordeeld zou worden voor zeven moorden in een ziekenhuis. ,,Zij sprak van een heksenjacht en wilde dat ik ernaar keek, zeker toen het ook een heksenproces werd, zoals ze dat noemde. Ze wees me erop dat statistiek als bewijs werd gebruikt en ik er dus wel iets van zou moeten vinden. Ik wilde niet. Er waren al ervaren statistici bij betrokken, ook mensen die ik kende.’’

Lucia de Berk reageert blij na haar vrijspraak © anp

Toen er in 2006 een boek over deze zaak verscheen, ging Gill overstag. ,,Ik werd door een collega op het boek gewezen. Ik wist werkelijk niet wat ik las, was er echt ondersteboven van. Voor mij was zonneklaar dat het vonnis niet deugde en de rechters de cijfers verkeerd hadden geïnterpreteerd.’’ 

De rest is geschiedenis. Gill hielp aantonen dat de cijfers de beschuldiging niet konden onderbouwen en Lucia werd na 6,5 jaar onterechte celstraf in 2010 volledig vrijgesproken.

Poggiali

Als hij in 2014 over een gelijksoortige situatie in Italië leest, besluit hij direct weer in actie te komen. Dit keer wordt een verpleegkundige (Daniela Poggiali) verdacht van zestig moorden. Gill belt zijn collega Julia Mortera van de Roma Tre-universiteit en samen bieden ze hun hulp aan. Met succes, ook deze verpleegkundige is na een eerdere veroordeling tot levenslange gevangenisstraf sinds oktober op vrije voeten.

Statistiek is de wetenschap en de techniek van het verzamelen, bewerken, interpreteren en presenteren van gegevens. Statistische methoden worden gebruikt om grote hoeveelheden gegevens – bijvoorbeeld over het koopgedrag van mensen, de huizenmarkt of het aantal doden in de zorg – om te zetten in bruikbare informatie.

,,De statistiek in deze zaak was totaal amateuristisch, het deugde niet. De aanklagers beweerden dat er meer sterfgevallen waren als Daniela werkte. Tot het moment dat ze werd gearresteerd: toen daalde het plotseling. Wij ontdekten dat het sterftecijfer bij alle personeelsleden hoog was. Daniela was vaak al voor het begin van haar ingeroosterde dienst aanwezig en bleef vaak ook nog helpen nadat haar dienst voorbij was. Daardoor was ze vaker aanwezig als een patiënt stierf. Dat het aantal doden daalde nadat Daniela werd gearresteerd, is simpel te verklaren. Het nieuws over de ‘moordzuster’ was breed uitgemeten in de media. Als gevolg daarvan trok het ziekenhuis minder patiënten. Minder patiënten betekent ook minder sterfgevallen.’’

Lastige kluif

Gill doet nu onderzoek naar de zware beschuldigingen tegen de Engelse verpleegkundige Ben Geen. Dat gebeurt op verzoek van zijn advocaat. Het is vooralsnog een heel lastige kluif, vooral omdat het rechtssysteem in Engeland anders in elkaar zit. Opnieuw is Gill ervan overtuigd dat de verdachte geen moorden heeft gepleegd en dat het recht moet zegevieren.

Uit deze zaken heeft hij belangrijke lessen getrokken die hij wil overbrengen aan iedereen die wereldwijd betrokken is bij de rechtspraak, van advocaten tot rechters en van officieren van justitie tot juryleden. Samen met andere experts schrijft hij een handleiding hoe statistiek in de rechtbank kan worden gebruikt, met name bij strafprocessen tegen zogeheten seriemoordenaars in de gezondheidszorg. Dat gebeurt onder supervisie van het gezaghebbende instituut Royal Statistical Society. Het boek moet later dit jaar verschijnen.

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Je kunt aannemen dat een hond vier poten heeft, maar niet dat alles met vier poten een hond is. Als op die manier naar Lucia was gekeken, was ze nooit veroordeeld

Richard Gill

De boodschap die hij heeft, is in hoofdlijnen simpel: gebruik statistische gegevens pas als je je ervan hebt verzekerd dat ze kloppen en gebruik ze goed. ,,Benoem alle factoren. Trek niet te snel conclusies. Vraag onafhankelijke experts om hulp. Onderzoek alle mogelijkheden.’’ Volgens Gill is niet alleen expertise van professionals nodig, maar ook dat rechters en advocaten worden geschoold in een goede interpretatie van statistieken.

Vier poten

Hij geeft een simpel voorbeeld. ,,Je kunt aannemen dat een hond vier poten heeft, maar niet dat alles met vier poten een hond is. Je mag aannemen dat iemand uit Peru Spaans spreekt, maar niet iedereen die Spaans spreekt komt uit Peru. Als op die manier naar Lucia was gekeken, was ze nooit veroordeeld.’’

Kenmerkend vindt Gill dat de verdachten die hij hielp, allemaal opvallende mensen zijn. Ze werkten hard, hadden een duidelijke mening, stootten daardoor waarschijnlijk ook leidinggevenden voor het hoofd en eindigden uiteindelijk als zondebok. ,,Het heeft me echt getroffen hoeveel ze gemeen hebben. Ben Geen wilde legerarts worden en was enorm gedreven in zijn werk. Hij zag zijn werk als meer dan een baan en deed veel extra als het kon. Hij botste ook met managers omdat het ziekenhuis voortdurend tegen grenzen aanliep.’’

Strafhof

Als expert op het terrein van statistieken werkte Gill ook voor het Openbaar Ministerie (moordzaak Tamara Wolvers) en het Internationaal Strafhof (moordaanslag president Libanon). Inmiddels is hij al bijna zes jaar gepensioneerd, maar tijd om zich te vervelen, heeft hij niet. Er ligt nog voor jaren werk op zijn bordje. Puzzels die hij graag helpt oplossen. 

Daarnaast zijn er veel onderwerpen waar hij graag in zou willen duiken, zoals de geruchtmakende Deventer moordzaak, die hem al jaren mateloos intrigeert. ,,Ik houd het nog steeds voor mogelijk dat de veroordeelde Ernest Louwes onschuldig is. Met name de dna-sporen op de blouse van de vermoorde weduwe vind ik interessant. Dna is ook statistisch bewijs en statistiek vertelt ons hoe je met onzekerheden moet omgaan. Er zijn inmiddels nieuwe moleculairbiologische methoden om veel meer uit een spoor te halen.’’

Omtzigt

Gill helpt Kamerlid Pieter Omtzigt met het analyseren van data over uithuisplaatsingen als gevolg van het toeslagenschandaal. ,,We maken een tijdlijn om oorzaak en gevolg in beeld te krijgen. Ik heb dus eigenlijk helemaal geen tijd meer om nog meer verpleegkundigen achter de tralies vandaan te halen’’, zegt hij met een glimlach.

Kamerlid Pieter Omtzigt. © ANP

Als er toch weer een zaak van een vermeende moordzuster op zijn pad komt, zal hij waarschijnlijk moeilijk ‘nee’ kunnen zeggen. Hij geniet van het puzzelen en wil voorkomen dat het leven saai wordt. De tekst op de achterkant van zijn trui spreekt wat dat betreft misschien wel boekdelen: ‘Keep calm, en deze opa lost het wel op’. Want ja. Gill, vader van drie kinderen, is opa en zijn vijf kleinkinderen logeren graag bij hem en zijn vrouw in Apeldoorn.

Julia-Lynn

Een van de vele puzzels die hem al jaren bezighoudt en soms zelfs uit zijn slaap haalt, moet hij van zichzelf oplossen: de zaak José Booij, die achttien jaar geleden werd geconfronteerd met de uithuisplaatsing van haar zes weken oude baby Julia-Lynn. 

,,Een onvoorstelbaar en afschuwelijk verhaal. Zij is vermalen door het systeem en daar compleet aan onderdoor gegaan. Ik ben het contact met José verloren, maar nog steeds in het bezit van een doos met persoonlijke spullen van haar, zoals kindertekeningen, diploma’s, dagboeken en krantenknipsels over haar strijd voor haar kind tot de hoogste rechtsorganen in Nederland en Europa aan toe. Wellicht leeft Julia-Lynn nu onder een andere naam en wellicht weet ze haar geboortenaam niet eens. Ik wil dat ze weet wie haar moeder is. Dat die nooit heeft opgegeven. Daar heeft ze recht op. Ik hoop haar ooit te vinden en de spullen van haar moeder te kunnen geven. En weet je, ook deze vrouw is een bijzonder mens, anders dan anderen.’

Interview

Published in “The Stentor” last Saturday, auto-translated from the original Dutch by Google Translate. This is the raw version. Corrections still to be made!

Richard Gill has already released two medical serial killers, including Lucia de Berk, by refuting statistical evidence. © Rob Voss

This Apeldoorn scientist saves innocent sisters from prison: Unfortunately, people do not want to believe in coincidence

Scientist Richard Gill from Apeldoorn helped ensure that Lucia de Berk was acquitted. He achieved the same in a similar case in Italy and now he is going for the hat trick in England. What drives him? 

Anne Boer 28-05-22, 08:00

Pure scientific curiosity is what drives him, says the internationally renowned mathematician Richard Gill from Apeldoorn. As an expert in statistics, Gill (70) worked for the Public Prosecution Service and the International Criminal Court. He has been retired for almost six years and is known as emeritus professor of statistics at Leiden University.

With his knowledge of the use of statistics, he was able to prove the innocence of two nurses who were convicted of serial murders from his office: the Dutch Lucia de Berk and the Italian Daniela Poggiali. Now he is campaigning for the release of nurse Ben Geen from England.

Sheer nonsense

All three are said to have killed patients on the job . Lucia de Berk was even convicted of seven murders. The burden of proof was mainly based on statistics. If Lucia worked, more patients would die than during her colleagues ‘ shifts. It turned out to be sheer nonsense, as Gill puts it delicately. “A matter of gossip and backbiting, looking for a scapegoat to save the hospital’s reputation and assumptions when no murder was committed at all. †

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Unfortunately, people do not want to believe in coincidence, we want to have a cause. That’s why we also believe in devils and gods

Statistical evidence plays a major role in research, including serial killers in the medical world. ,,But then you have to interpret the figures properly ” , says Gill. “If apparently many people die in a hospital, you first have to look closely at the cause. Are there perhaps more patients than usual ? Are they sicker than in other periods? Has the registration method been adjusted? Are there changes in the staff? If you immediately look at which nurse was present, you also skip the most important questions: is it murder or is it medical failure or even natural death? †

According to Gill, that immediately touches on another sore point. “A hospital is a place where people die, but often the cause of death is not clear. This can lead to clusters of suspicious deaths. You have to know which deaths you count, otherwise the police will look for evidence for claims. †

Passionate

According to Gill, you should always keep in mind that there can be a good, innocent reason for an event. “Look at how often someone works. Full-time nurses experience more deaths than part-time nurses. If someone works full-time and is passionate about their craft, they’re even more likely to be there when someone dies than someone who works a few days a week or works strictly within the schedule. †

Scientist Richard Gill. © Rob Voss

According to him, you should never rule out a strange combination of circumstances. “They happen, even without murder. A famous example is an American couple who won the top prize in two different lotteries in one day . What are the chances of something like this happening? It really happened. Unfortunately, people do not want to believe in coincidence, we want to have a cause and look for a scapegoat. That is why we also believe in devils and gods. †

Love

Richard Gill was born in England. His father was also a scientist. Love brought him to the Netherlands in 1974 at the age of 23. Six years earlier, on holiday, he had fallen head over heels for a daughter of a Dutch friend of his father’s. Both fathers work for Wavin from Hardenberg. After some wanderings, Gill ends up in Apeldoorn in the early 1980s, never to leave. He lives in an old mansion, in a sea of lush greenery. This was his wife’s childhood home. To keep his head above water financially, he works extra hard to make a quick career .

The medical world crosses his path early on. After studying mathematics at Cambridge, he obtained his doctorate for research into the question of how long cancer patients survive with a particular treatment. His calculation method turned out to be a godsend and is now also being applied in other areas. “It just happened to be on my plate. I didn’t have a topic and my promoter took this topic out of his drawer. It has had a lot of impact and the method is still widely used. †

witch hunt

His wife, who is a historian, points him at an early stage to the case of Lucia de Berk, who would later be convicted of seven murders in a hospital. “She spoke of a witch hunt and wanted me to watch it, especially when it became a witch trial, as she called it. She pointed out to me that statistics were used as evidence and so I should have something to say about it. I did not want to. Experienced statisticians were already involved, including people I knew. †

Lucia de Berk reacts happy after her acquittal © anp

When a book about this case was published in 2006, Gill took the plunge. “I was referred to the book by a colleague. I really didn’t know what I was reading, I was really blown away by it. It was crystal clear to me that the verdict was wrong and that the judges had misinterpreted the figures . †

The rest is history. Gill helped show that the figures failed to substantiate the accusation and Lucia was fully acquitted in 2010 after 6.5 years of wrongful imprisonment.

poggiali

reads about a similar situation in Italy in 2014 , he immediately decides to jump back into action. This time, a nurse (Daniela Poggiali) is suspected of sixty murders. Gill calls his colleague Julia Mortera from Roma Tre University and together they offer their help. With success, this nurse has also been free since October after a previous sentence to life imprisonment.

Statistics is the science and technology of collecting, processing, interpreting and presenting data. Statistical methods are used to convert large amounts of data – for example about people’s purchasing behaviour, the housing market or the number of deaths in care – into useful information .

,,The statistics in this case were completely amateurish, it was not good. Prosecutors claimed there were more deaths when Daniela worked. Until she was arrested: then it suddenly dropped. We found that the death rate for all staff was high. Daniela was often present before the start of her scheduled shift and often continued to help after her shift was over. As a result, she was more often present when a patient died . It is easy to explain that the number of deaths decreased after Daniela was arrested. The news about the ‘ murder sister ‘ was widely covered in the media. As a result, the hospital attracted fewer patients . Fewer patients also means fewer deaths. †

Difficult bone

Gill is now investigating the serious allegations against English nurse Ben Geen. This is done at the request of his lawyer. It is still a very difficult task, especially because the legal system in England is different. Once again, Gill is convinced that the suspect committed no murders and that justice must prevail.

He has learned important lessons from these cases that he wants to pass on to everyone involved in the justice system worldwide, from lawyers to judges and from prosecutors to jurors. Together with other experts, he is writing a manual on how to use statistics in court, especially in criminal proceedings against so-called serial killers in healthcare. This is done under the supervision of the authoritative Royal Statistical Society. The book is due out later this year.

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You can assume that a dog has four legs, but not everything with four legs is a dog. If Lucia had been looked at that way, she would never have been judged

Richard Gill

The message he has is basically simple: do not use statistical data until you have ensured that they are correct and use them well. “Name all the factors. Don’t jump to conclusions too quickly. Ask independent experts for help. Explore all possibilities. ” According to Gill, not only expertise from professionals is needed, but also that judges and lawyers are trained in a good interpretation of statistics.

Four legs

He gives a simple example. “You can assume that a dog has four legs, but not that everything with four legs is a dog. You can assume that someone from Peru speaks Spanish, but not everyone who speaks Spanish is from Peru. If Lucia had been looked at that way, she would never have been convicted. †

Typically, Gill finds that the suspects he helped are all striking people. They worked hard, had strong opinions, probably offended executives as a result, and ended up as scapegoats. “It really struck me how much they have in common. Ben Geen wanted to be an army doctor and was very passionate about his work. He saw his work as more than a job and did a lot extra when he could. He also clashed with managers because the hospital was constantly running into limits. †

criminal court

As an expert in statistics, Gill also worked for the Public Prosecution Service (Tamara Wolvers murder case) and the International Criminal Court (Lebanon Presidential assassination attempt). He has now been retired for almost six years, but he has no time to get bored. There is still work on his plate for years to come. Puzzles he likes to help solve. 

In addition, there are many subjects that he would like to delve into, such as the controversial Deventer murder case, which has intrigued him immensely for years. “I still think it possible that the convicted Ernest Louwes is innocent. I find the DNA traces on the murdered widow’s blouse particularly interesting. DNA is also statistical evidence and statistics tells us how to deal with uncertainties. There are now new molecular biological methods to get much more out of a track. †

omtzigt

Gill helps MP Pieter Omtzigt with analyzing data about custodial placements as a result of the benefits scandal. ,,We make a timeline to get a picture of cause and effect. So I don’t really have time to get any more nurses out of prison , ” he says with a smile.

Member of Parliament Pieter Omtzigt. © ANP

If a case of an alleged murder sister comes his way, he will probably have a hard time saying ‘ no ‘ . He enjoys puzzling and wants to prevent life from getting boring. The text on the back of his sweater might speak volumes in that regard: ‘ Keep calm, and this grandpa will solve it ‘ . Because yes. Gill, a father of three, is a grandfather and his five grandchildren like to stay with him and his wife in Apeldoorn.

Julia-Lynn

He has to solve one of the many puzzles that has occupied him for years and sometimes even wakes him up: the case of Jos é Booij, who was confronted eighteen years ago with the custodial placement of her six-week-old baby Julia-Lynn.

“An unbelievable and horrifying story. She was crushed by the system and completely destroyed by it. I have lost contact with José , but I still have a box with her personal items, such as children’s drawings, diplomas , diaries and newspaper clippings about her fight for her child up to the highest courts in the Netherlands and Europe. . Julia-Lynn may be living under a different name now and may not even know her birth name. I want her to know who her mother is. That he never gave up. She is entitled to that. I hope one day to find her and give her mother’s things. And you know, this woman is also a special person, different from others. †

José, Kevin, Lucia (JKL)

More than ten years ago I started writing a book on Dutch miscarriages of justice in which I had been involved. I wanted to explore the personality issues in three such cases. In each case, it seemed to me that aspects of the character of the main protagonist led to them being something of a scapegoat of a system under great stress. Some trigger events caused a bad situation to become an utter disaster. Authorities made mistakes and could not admit them, so errors were compounded, and there was no going back, no way to change path any more.

In recent posts, I have told a lot of the story of José Booij. It’s time to start writing about Lucia de Berk and Kevin Sweeney.

Concerning Lucia de Berk there already is an enormous literature. The case started in 2001, seemed to be closed with Lucia in jail for life by 2006 (conviction by the lower court at the first trial in 2003, appeal to higher court failed in 2004, cassation – appeal to the supreme court – failed in 2006) but at that time also a strong movement burst into the public view, calling for a judicial review and a retrial. Lucia was fully exonerated in 2010. The role of statistics in the case is well known though controversial since at the 2004 appeal, she was convicted “on the grounds of incontrovertible medical scientific evidence only”. A “statistical probability calculation” (such as the infamous calculation leading to the spectacular 1 in 342 million) played no part at all in the court’s conclusion, according to her judges.

Yet many things have still not been said in public about the case, except perhaps in literary form. In my future book, I want to say things I have said many times before in ephemeral blog posts, and other removed or hidden web pages.

Concerning Kevin Sweeney, not much has been written at all. He sat out his sentence for the murder of his wife and keeps a low profile.

Condemned by statisticians?

A Bayesian analysis of the case of Lucia de B.

de Vos, A. F. (2004).

Door statistici veroordeeld? Nederlands Juristenblad, 13, 686-688.


Here, the result of Google-translate by RD Gill; with some “hindsight comments” by him added in square brackets and marked “RDG”.


Would having posterior thoughts
Not be offending the gods?
Only the dinosaur
Had them before
Recall its fate! Revise your odds!
(made for a limerick competition at a Bayesian congress).

The following article was the basis for two full-page articles on Saturday, March 13, 2004 in the science supplement of the NRC (with unfortunately disturbing typos in the ultimate calculation) and in “the Forum” of Trouw (with the expected announcement on the front page that I claimed that the chance that Lucia de B. was wrongly convicted was 80%, which is not the case)

Condemned by statisticians?
Aart F. de Vos

Lucia de Berk [Aart calls her “Lucy” in his article. That’s a bit condescending – RDG] has been sentenced to life imprisonment. Statistical arguments played a role in that, although the influence of this in the media was overestimated. Many people died while she was on duty. Pure chance? The consulted statistician, Henk Elffers, repeated his earlier statement during the current appeal that the probability was 1 in 342 million. I quote from the article “Statisticians do not believe in coincidence” from the Haags Courant of January 30th: “The probability that nine fatal incidents took place in the JKZ during the shifts of the accused by pure chance is nil. (…) It wasn’t chance. I don’t know what it was. As a statistician, I can’t say anything about it. Deciding the cause is up to you”. The rest of the article showed that the judge had great difficulty with this answer, and did not manage to resolve those difficulties.

Many witnesses were then heard who talked about circumstances, plausibility, oddities, improbabilities and undeniably strong associations. The court has to combine all of this and arrive at a wise final judgment. A heavy task, certainly given the legal conceptual system that includes very many elements that have to do with probabilities but has to make do without quantification and without probability theory when combining them.

The crucial question is of course: how likely is it that Lucia de Berk committed murders? Most laypeople will think that Elffers answered that question and that it is practically certain.

This is a misunderstanding. Elffers did not answer that question. Elffers is a classical statistician, and classical statisticians do not make statements about what is actually going on, but only about how unlikely things are if nothing special is going on at all. However, there is another branch of statistics: the Bayesian. I belong to that other camp. And I’ve also been doing calculations. With the following bewildering result:

If the information that Elffers used to reach his 1 in 342 million were the only information on which Lucia de Berk was convicted, I think that, based on a fairly superficial analysis, there would be about an 80% chance of the conviction being wrong.

This article is about this great contrast. It is not an indictment of Elffers, who was extremely modest in the court when interpreting his outcome, nor a plea to acquit Lucia de Berk, because the court uses mainly different arguments, albeit without unequivocal statements of probability, while there is nothing which is absolutely certain. It is a plea to seriously study Bayesian statistics in the Netherlands, and this applies to both mathematicians and lawyers. [As we later discovered, many medical experts’ conclusions that certain deaths were unnatural was caused by their knowledge that Lucia had been present at an impossibly huge number of deaths – RDG]

There is some similarity to the Sally Clark case, which was sentenced to life imprisonment in 1999 in England because two of her sons died shortly after birth. A wonderful analysis can be found in the September 2002 issue of “living mathematics”, an internet magazine (http://plus.maths.org/issue21/features/clark/index.html)

An expert (not a statistician, but a doctor) explained that the chance that such a thing happened “just by chance” in the given circumstances was 1 in 73 million. I quote: “probably the most infamous statistical statement ever made in a British courtroom (…) wrong, irrelevant, biased and totally misleading.” The expert’s statement is completely torn to shreds in said article. Which includes mention of a Bayesian analysis. And a calculation that the probability that she was wrongly convicted was greater than 2/3. In the case of Sally Clark, the expert’s statement was completely wrong on all counts, causing half the nation to fall over him, and Sally Clark, though only after four years, was released. However, the case of Lucia de Berk is infinitely more complicated. Elffers’ statement is, I will argue, not wrong, but it is misleading, and the Netherlands has no jurisprudence, but judgments, and even though they are not directly based on extensive knowledge of probability theory, they are much more reasoned. That does not alter the fact that there is a common element in the Lucy de Berk and Sally Clark cases. [Actually, Elffers’ statement was wrong in its own terms. Had he used the standard and correct way to combine p-values from three separate samples, he would have ended up with a p-value of about 1/1000. Had he verified the data given him by the hospital, it would have been larger still. Had he taken account of heterogeneity between nurses and uncertainty in various estimates, both of which classical statisticians also know how to do too, larger still – RDG]

Bayesian statistics

My calculations are therefore based on alternative statistics, the Bayesian, named after Thomas Bayes, the first to write about “inverse probabilities”. That was in 1763. His discovery did not become really important [in statistics] until after 1960, mainly through the work of Leonard Savage, who proved that when you make decisions under uncertainty you cannot ignore the question of what chances the possible states of truth have (in our case the states “guilty” and “not guilty”). Thomas Bayes taught us how you can learn about that kind of probability from data. Scholars agree on the form of those calculations, which is pure probability theory. However, there is one problem: you have to think about what probabilities you would have given to the possible states before you had seen your data (the prior). And often these are subjective probabilities. And if you have little data, the impact of those subjective probabilities on your final judgment is large. A reason for many classical statisticians to oppose this approach. Certainly in the Netherlands, where statistics is mainly practised by mathematicians, people who are trained to solve problems without wondering what they have to do with reality. After a fanatical struggle over the foundations of statistics for decades (see my piece “the religious war of statisticians” at http://staff.feweb.vu.nl/avos/default.htm) the parties have come closer together. With one exception: the classical hypothesis test (or significance test). Bayesians have fundamental objections to classical hypothesis tests. And Elffers’ statement takes the form of a classical hypothesis test. This is where the foundations debate focuses.

The Lucy Clog case

Following Elffers, who explained his method of calculation in the Nederlands Juristenblad on the basis of a fictional case “Klompsma” which I have also worked through (arriving at totally different conclusions), I want to talk about the fictional case Lucy Clog [“Klomp” is the Dutch word for “clog”; the suffix “-sma” indicates a person from the province of Groningen; this is all rather insulting – RDG]. Lucy Clog is a nurse who has experienced 11 deaths in a period in which on average only one case occurs, but where no further concrete evidence against her can be found. In this case too, Elffers would report an extremely small chance of coincidence in court, about 1 in 100 million [I think that de Vos is thinking of the Poisson(1) chance of at least 11 events. If so, it is actually a factor 10 smaller. Perhaps he should change “11 deaths” into “10 deaths” – RDG]. This is the case where I claim that a guilty conviction, given the information so far together with my assessment of the context, has a chance of about 80% of being wrong.

This requires some calculations. Some of them are complicated, but the most important aspect is not too difficult, although it appears that many people struggle with it. A simple example may make this key point clear.

You are at a party and a stranger starts telling you a whole story about the chance that Lucia de Berk is guilty, and embarks joyfully on complex arithmetical calculations. What do you think: is this a lawyer or a mathematician? If you say a mathematician because lawyers are usually unable to do mathematics, then you fall into a classical trap. You think: a mathematician is good at calculations, while the chance that a lawyer is good at calculations is 10%, so it must be a mathematician. What you forget is that there are 100 times more lawyers than mathematicians. Even if only 10% of lawyers could do this calculating stuff, there would still be 10 times as many lawyers as mathematicians who could do it. So, under these assumptions, the probability is 10/11 that it is a lawyer. To which I must add that (I think) 75% of mathematicians are male but only 40% of lawyers are male, and I did not take this into account. If the word “she” had been in the problem formulation, that would have made a difference.

The same mistake, forgetting the context (more lawyers than mathematicians), can be made in the case of Lucia de Berk. The chance that you are dealing with a murderous nurse is a priori (before you know what is going on) very much smaller than that you are dealing with an innocent nurse. You have to weigh that against the fact that the chance of 11 deaths is many times greater in the case of “murderous” than in the case of “innocent”.

The Bayesian way of performing the calculations in such cases also appears to be intuitively not easy to understand. But if we look back on the example of the party, maybe it is not so difficult at all.

The Bayesian calculation is best not done in terms of chances, but in terms of “odds”, an untranslatable word that does not exist in the Netherlands. Odds of 3 to 7 mean a chance of 3/10 that it is true and 7/10 that it is not. Englishmen understand what this means perfectly well, thanks to horse racing: odds of 3 to 7 means you win 7 if you are right and lose 3 if you are wrong. Chances and odds are two ways to describe the same thing. Another example: odds of 2 to 10 correspond to probabilities of 2/12 and 10/12.

You need two elements for a simple Bayesian calculation. The prior odds and the likelihood ratio. In the example, the prior odds are mathematician vs. lawyer 1 to 100. The likelihood ratio is the probability that a mathematician does calculations (100%) divided by the probability that a lawyer does (10%). So 10 to 1. Bayes’ theorem now says that you must multiply the prior odds (1 : 100) and the likelihood ratio (10 : 1) to get the posterior odds, so they are (1 x 10 : 100 x 1) = (10 : 100) = (1 : 10), corresponding to a probability of 1 / 11 that it is a mathematician and 10/11 that it is a lawyer. Precisely what we found before. The posterior odds are what you can say after the data are known, the prior odds are what you could say before. And the likelihood ratio is the way you learn from data.

Back to the Lucy Clog case. If the chance of 11 deaths is 1 in 100 million when Lucy Clog is innocent, and 1/2 when she is guilty – more about that “1/2” much later – then the likelihood ratio for innocent against guilty is 1 : 50 million. But to calculate the posterior probability of being guilty, you need the prior odds. They follow from the chance that a random nurse will commit murders. I estimate that at 1 to 400,000. There are forty thousand nurses in hospitals in the Netherlands, so that would mean nursing killings once every 10 years. I hope that is an overestimate.

Bayes’ theorem now says that the posterior odds of “innocent” in the event of 11 deaths would be 400,000 to 50 million. That’s 8 : 1000, so a small chance of 8/1008, maybe enough to convict someone. Yet large enough to want to know more. And there is much more worth knowing.

For instance, it is remarkable that nobody saw Lucy doing anything wrong. It is even stranger when further investigation yields no evidence of murder. If you think that there would still be an 80% chance of finding clues in the event of many murders, against of course 0% if it is a coincidence, then the likelihood ratio of the fact “no evidence was found” is 100 : 20 in favour of innocence. Application of the rule shows that we now have odds of 40 : 1000, so a small 4% chance of innocence. Conviction now becomes really questionable. And if the suspect continues to deny, which is more plausible when she is innocent than when she is guilty, say twice as plausible, the odds turn into 80 : 1000, almost 8% chance of innocence.

As an explanation, a way of looking at this that requires less calculation work (but says exactly the same thing) is as follows: It follows from the assumptions that in 20,000 years it occurs 1008 times that 11 deaths occur in a nurse’s shifts: 1,000 of the nurses are guilty and 8 are innocent. Evidence for murder is found for 800 of the guilty nurses, moreover, 100 of the remaining 200 confess. That leaves 100 guilty and 8 innocent among the nurses who did not confess and for whom no evidence for murder was found.

So Lucy Clog must be acquitted. And all the while, I haven’t even talked about doubts about the exact probability of 1 in 100 million that “by chance” 11 people die in so many nurses’ shifts, when on average it would only be 1. This probability would be many times higher in every Bayesian analysis. I estimate, based on experience, that 1 in 2 million would come out. A Bayesian analysis can include uncertainties. Uncertainties about the similarity of circumstances and qualities of nurses, for example. And uncertainties increase the chance of extreme events enormously, the literature contains many interesting examples. As I said, I think that if I had access to the data that Elffers uses, I would not get a chance of 1 in 100 million, but a chance of 1 in 2 million. At least I assume that for the time being; it would not surprise me if it were much higher still!

Preliminary calculations show that it might even be as high as 1 in 100,000. But 1 in 2 million already saves a factor of 50 compared to 1 in 100 million, and my odds would not be 80 to 1000 but 4000 to 1000, so 4 to 1. A chance of 80% to wrongly convict. This is the 80% chance of innocence that I mentioned in the beginning. Unfortunately, it is not possible to explain the factor 50 (or a factor 1000 if the 1 in 100,000 turns out to be correct) from the last step within the framework of this article without resorting to mathematics. [Aart de Vos is probably thinking of Poisson distributions, but adding a hyperprior over the Poisson mean of 1, in order to take account of uncertainty in the true rate of deaths, as well as heterogeneity between nurses, causing some to have shifts with higher death rates than others – RDG]

What I hope has become clear is that you can always add information. “Not being able to find concrete evidence of murder” and “has not confessed” are new pieces of evidence that change the odds. And perhaps there are countless facts to add. In the case of Lucia de Berk, those kinds of facts are there. In the hypothetical case of Lucy Clog, not.

The fact that you can always add information in a Bayesian analysis is the most beautiful aspect of it. From prior odds, you come through data (11 deaths) to posterior odds, and these are again prior odds for the next steps: no concrete evidence for murder, and no confession by our suspect. Virtually all further facts that emerge in a court case can be dealt with in this way in the analysis. Any fact that has a different probability under the hypothesis of guilt than under the hypothesis of innocence contributes. Perhaps the reader has noticed that we only talked about the chances of what actually happened under various hypotheses, never about what could have happened but didn’t. A classic statistical test always talks about the probability of 11 or more deaths. That “or more” is irrelevant and misleading according to Bayesians. Incidentally, it is not necessarily easier to just talk about what happened. What is the probability of exactly 11 deaths if Lucy de Clog is guilty? The number of murders, something with a lot of uncertainty about it, determines how many deaths there are, but even though you are fired after 11 deaths, the classical statistician talks about the chance of you committing even more if you are kept on. And that last fact matters for the odds. That’s why I put in a probability of 50%, not 100%, for a murderous nurse killing exactly 11 patients. But that only makes a factor 2 difference.

It should be clear that it is not easy to come to firm statements if there is no convincing evidence. The most famous example, for which many Bayesians have performed calculations, is a murder in California in 1956, committed by a black man with a white woman in a yellow Cadillac. A couple who met this description was taken to court, and many statistical analyses followed. I have done a lot of calculations on this example myself, and have experienced how difficult, but also surprising and satisfying, it is to constantly add new elements.

A whole book is devoted to a similar famous case: “a Probabilistic Analysis of the Sacco and Vanzetti Evidence,” published in 1996 by Jay Kadane, professor of Carnegie Mellon and one of the most prominent Bayesians. If you want to know more, just consult his c.v. on his website http://lib.stat.cmu.edu/~kadane. In the “Statistics and the Law” field alone, he has more than thirty publications to his name, along with hundreds of other articles. This is now a well-developed field in America.

Conclusion?

I have thought for a long time about what the conclusion of this story is, and I have had to revise my opinion several times. And the perhaps surprising conclusion is: the actions of all parties are not that bad, only their rationalization is, to put it mildly, a bit strange. Elffers makes strange calculations but formulates the conclusions in court in such a way that it becomes intuitively clear that he is not giving the answer that the court is looking for. The judge makes judgments that sound as though they are in terms of probabilities but I cannot figure out what the judge’s probabilities are. But when I see what is going on I do get the feeling that it is much more like what is optimal than I would have thought possible, given the absurd rationalisations. The explanation is simple: judges’ actions are based on a process learnt by evolution, judges’ justifications are stuck on afterwards, and learnt through training. In my opinion, the Bayesian method is the only way to balance decisions under uncertainty about actions and rationalization. And that can be very fruitful. But the profit is initially much smaller than people think. What the court does in the case of Lucia de B is surprisingly rational. The 11 deaths are not convincing in themselves, but enough to change the prior odds from 1 in 40,000 to odds from 16 to 5, in short, an order of magnitude in which it is necessary to gather additional information before judging. Exactly what the court does. [de Vos has an optimistic view. He does not realise that the court is being fed false facts by the hospital managers – they tell the truth but not the whole truth; he does not realise that Elffers’ calculation was wrong because de Vos, as a Bayesian, doesn’t know what good classical statisticians do; neither he nor Elffers checks the data and finds out how exactly it was collected; he does not know that the medical experts’ diagnoses are influenced by Elffers’ statistics. Unfortunately, the defence hired a pure probabilist, and a kind of philosopher of probability, neither of whom knew anything about any kind of statistics, whether classical or Bayesian – RDG]

When I made my calculations, I thought at times: I have to go to court. I finally sent the article but I heard nothing more about it. It turned out that the defence had called for a witness who seriously criticized Elffers’ calculations. However, without presenting the solution. [The judge found the defence witness’s criticism incomprehensible, and useless to boot. It contained no constructive elements. But without doing statistics, anybody could see that the coincidence couldn’t be pure chance. It wasn’t: one could say that the data was faked. On the other hand, the judge did understand Elffers perfectly well – RDG].


Maybe I will once again have the opportunity to fully calculate probabilities in the Lucia de Berk case. That could provide new insights. But it is quite a job. In this case, there is much more information than is used here, such as poisonous traces in patients. Here too, it is likely that a Bayesian analysis that takes into account all the uncertainties shows that statements by experts who say something like “it is impossible that there is another explanation than the administration of poison by Lucia de Berk” should be taken with a grain of salt. Experts are usually people who overestimate their certainty. On the other hand, incriminating information can also build up. Ten independent facts that are twice as likely under the hypothesis of guilt change the odds by a factor of 1000. And if it turns out that the toxic traces found in the bodies of five deceased patients are each nine times more likely if Lucia is a murderer than if she isn’t, it saves a factor of nine to the fifth, a small 60,000. Etc, etc

But I think the court is more or less like that. It uses an incomprehensible language, that is, incomprehensible to probabilists, but a language sanctioned by evolution. We have few cases of convictions that were found to be wrong in the Netherlands. [Well! That was a Dutch layperson, writing in 2004. According to Ton Derksen, in the Netherlands about 10% of very long term prisoners (very serious cases) are innocent. It is probably something similar in other jurisdictions – RDG].

If you did the entire process in terms of probability calculations, the resulting debates between prosecutors and lawyers would become endless. And given their poor knowledge of probability, it is also undesirable for the time being. They have their secret language that usually led to reasonable conclusions. Even the chance that Lucia de Berk is guilty cannot be expressed in their language. There is also no law in the Netherlands that defines “legal and convincing evidence” in terms of the chance that a decision is correct. Is that 95%? Or 99%? Judges will maintain that it is 99.99%. But judges are experts.

So I don’t think it’s wise to try to cast the process in terms of probability right now. But perhaps this discussion will produce something in the longer term. Judges who are well informed about the statistical significance of the starting situation and then write down a number for each piece of evidence of prosecutor and defender. The likelihood ratio of each fact must be motivated. At the end, multiply all these numbers together, and have the calculations checked again by a Bayesian statistician. However, I consider this a long-term perspective. I fear (I am not really young anymore) it won’t come in my lifetime.

BOLC (Bureau Verloren Zaken) “reloaded”

Het BOLC is weer terug.

10 jaar geleden (in 2010) werd de Nederlandse verpleegster Lucia de Berk bij een nieuw proces vrijgesproken van een aanklacht van 7 moorden en 3 pogingen tot moord in ziekenhuizen in Den Haag in een aantal jaren in de aanloop naar slechts een paar dagen voor de gedenkwaardige datum van “9-11”. De laatste moord zou in de nacht van 4 september 2001 zijn gepleegd. De volgende middag meldden de ziekenhuisautoriteiten een reeks onverklaarbare sterfgevallen aan de gezondheidsinspectie en de politie. Ook plaatsten ze Lucia de B., zoals ze bekend werd in de Nederlandse media, op ‘non-active’. De media meldden dat er ongeveer 30 verdachte sterfgevallen en reanimaties werden onderzocht. De ziekenhuisautoriteiten meldden niet alleen wat volgens hen vreselijke misdaden waren, ze geloofden ook dat ze wisten wie de dader was.

De wielen van gerechtigheid draaien langzaam, dus er was een proces en een veroordeling; een beroep en een nieuw proces en een veroordeling; eindelijk een beroep op het hooggerechtshof. Het duurde tot 2006 voordat de veroordeling (levenslange gevangenisstraf, die in Nederland pas wordt beëindigd als de veroordeelde de gevangenis verlaat in een kist) onherroepelijk wordt. Alleen nieuw bewijs kan het omverwerpen. Nieuwe wetenschappelijke interpretaties van oud bewijs worden niet als nieuw bewijs beschouwd. Er was geen nieuw bewijs.

Maar al, in 2003-2004, maakten sommige mensen met een interne band met het Juliana Kinderziekenhuis zich al zorgen over de zaak. Nadat ze in vertrouwen met de hoogste autoriteiten over hun zorgen hadden gesproken, maar toen ze te horen kregen dat er niets aan te doen was, begonnen ze journalisten te benaderen. Langzaam maar zeker raakten de media weer geïnteresseerd in de zaak – het verhaal was niet meer het verhaal van de vreselijke heks die baby’s en oude mensen zonder duidelijke reden had vermoord, behalve voor het plezier in het doden, maar van een onschuldige persoon die was verminkt door pech, incompetente statistieken en een monsterlijk bureaucratisch systeem dat eens in beweging, niet kon worden gestopt.

Onder de supporters van Metta de Noo en Ton Derksen waren enkele professionele statistici, omdat Lucia’s aanvankelijke veroordeling was gebaseerd op een foutieve statistische analyse van door het ziekenhuis verstrekte onjuiste gegevens en geanalyseerd door amateurs en verkeerd begrepen door advocaten. Anderen waren informatici, sommigen waren ambtenaren op hoog niveau van verschillende overheidsorganen die ontsteld waren over wat ze zagen gebeuren; er waren onafhankelijke wetenschappers, een paar medisch specialisten, een paar mensen met een persoonlijke band met Lucia (maar geen directe familie); en vrienden van zulke mensen. Sommigen van ons werkten vrij intensief samen en werkten met name aan de internetsite voor Lucia, bouwden er een Engelstalige versie van en brachten deze onder de aandacht van wetenschappers over de hele wereld. Toen kranten als de New York Times en The Guardian begonnen te schrijven over een vermeende gerechtelijke dwaling met verkeerd geïnterpreteerde statistieken, ondersteund door opmerkingen van Britse topstatistici, hadden de Nederlandse journalisten nieuws voor de Nederlandse kranten, en dat soort nieuws werd zeker opgemerkt in de gangen van de macht in Den Haag.

Snel vooruit naar 2010, toen rechters niet alleen Lucia onschuldig verklaarden, maar voor de rechtszaal hard-op verklaarden dat Lucia samen met haar collega-verpleegkundigen uiterst professioneel had gevochten om het leven van baby’s te redden die onnodig in gevaar werden gebracht door medische fouten van de medisch specialisten die waren belast met hun zorg. Ze vermeldden ook dat alleen omdat het tijdstip van overlijden van een terminaal zieke persoon niet van tevoren kon worden voorspeld, dit niet betekende dat het noodzakelijkerwijs onverklaarbaar en dus verdacht was.

Enkelen van ons, opgetogen door onze overwinning, besloten om samen te werken en een soort collectief te vormen dat zou kijken naar andere ‘verloren zaken’ met mogelijke justitiele dwalingen waar de wetenschap misbruikt was. Ik had al had mijn eigen onderzoeksactiviteiten omgebogen en gericht op het snelgroeiende veld van forensische statistiek, en ik was al diep betrokken bij de zaak Kevin Sweeney en de zaak van José Booij. Al snel hadden we een website en waren we hard aan het werk, maar kort daarna gebeurde er een opeenvolging van ongelukken. Ten eerste betaalde het ziekenhuis van Lucia een dure advocaat om me onder druk te zetten namens de hoofdkinderarts van het Juliana Children’s Hospital. Ik had namelijk wat persoonlijke informatie over deze persoon (die toevallig de schoonzus was van Metta de Noo en Ton Derksen) geschreven op mijn homepage aan de Universiteit van Leiden. Ik voelde dat het van cruciaal belang was om te begrijpen hoe de zaak tegen Lucia was begonnen en dit had zeker veel te maken met de persoonlijkheden van enkele sleutelfiguren in dat ziekenhuis. Ik schreef ook naar het ziekenhuis en vroeg om meer gegevens over de sterfgevallen en andere incidenten op de afdelingen waar Lucia had gewerkt, om het professionele onafhankelijke statistische onderzoek te voltooien dat had moeten plaatsvinden toen de zaak begon. Ik werd bedreigd en geïntimideerd. Ik vond enige bescherming van mijn eigen universiteit die namens mij dure advocatenkosten betaalde. Mijn advocaat adviseerde me echter al snel om toe te geven door aanstootgevend materiaal van internet te verwijderen, want als dit naar de rechtbank zou gaan, zou het ziekenhuis waarschijnlijk winnen. Ik zou de reputatie van rijke mensen en van een machtige organisatie schaden en ik zou moeten boeten voor de schade die ik had aangericht. Ik moest beloven om deze dingen nooit weer te zeggen en ik zou beboet worden als ze ooit herhaald zou worden door anderen. Ik heb nooit toegegeven aan deze eisen. Later heb ik wel wat gepubliceerd en naar het ziekenhuis opgestuurd. Ze bleven stil. Het was een interessante spel bluf poker.

Ten tweede schreef ik op gewone internetfora enkele zinnen waarin ik José Booij verdedigde, maar die de persoon die haar bij de kinderbescherming had aangegeven ook van schuld verweet. Dat was geen rijk persoon, maar zeker een slim persoon, en ze meldden mij bij de politie. Ik werd verdachte in een geval van vermeende laster. Geïnterviewd door een aardige lokale politieagent. En een paar maanden later kreeg ik een brief van de lokale strafrechter waarin stond dat als ik 200 euro administratiekosten zou betalen, de zaak administratief zou worden afgesloten. Ik hoefde geen schuld te bekennen maar kon ook niet aantekenen dat ik me onschuldig vond.

Dit leidde ertoe dat het Bureau Verloren Zaken zijn activiteiten een tijdje stopzette. Maar het is nu tijd voor een come-back, een “re-boot”. Ondertussen deed ik niet niets, maar raakte ik betrokken bij een half dozijn andere zaken, en leerde ik steeds meer over recht, over forensische statistiek, over wetenschappelijke integriteit, over organisaties, psychologie en sociale media. De BOLC is terug.

ORGANISATIE en PLANNEN

Het BOLC is al een paar jaar inactief, maar nu de oprichter de officiële pensioenleeftijd heeft bereikt, “herstart” hij de organisatie. Richard Gill richtte de BOLC op aan de vooravond van de vrijspraak van verpleegster Lucia de Berk in 2006. Een groep vrienden die nauw betrokken waren geweest bij de beweging om Lucia een eerlijk proces te bezorgen, besloten dat ze zo genoten van elkaars gezelschap en zoveel hadden geleerd van de ervaring van de afgelopen jaren, dat ze hun vaardigheden wilden uitproberen op enkele nieuwe cases. We kwamen snel een aantal ernstige problemen tegen en stopten onze website tijdelijk, hoewel de activiteiten in verschillende gevallen werden voortgezet, meer ervaring werd opgedaan, veel werd geleerd.

We vinden dat het tijd is om het opnieuw te proberen, nadat we enkele nuttige lessen hebben geleerd van onze mislukkingen van de afgelopen jaren. Hier is een globaal overzicht van onze plannen.

  1. Zet een robuuste formele structuur op met een bestuur (voorzitter, secretaris, penningmeester) en een adviesraad. In plaats van het de wetenschappelijke adviesraad te noemen, zoals gebruikelijk in academische organisaties, zou het een morele en / of wijsheidsadviesraad moeten zijn om op de hoogte te worden gehouden van onze activiteiten en ons te laten weten als ze denken dat we van de rails gaan.
  2. Eventueel een aanvraag indienen om een Stichting te worden. Dit betekent dat we ook zoiets zijn als een vereniging of een club, met een jaarlijkse algemene vergadering. We zouden leden hebben, die misschien ook donaties willen doen, aangezien het runnen van een website en het af en toe in de problemen komen geld kost.
  3. Schrijf over de zaken waar we de afgelopen jaren bij betrokken zijn geweest, met name: vermeende seriemoordenaars Ben Geen (VK), Daniela Poggiali (Italië); beschuldigingen van wetenschappelijk wangedrag in het geval van het proefschrift van een student van Peter Nijkamp; het geval van de AD Haring-test en de kwaliteit van Dutch New Herring; het geval van Kevin Sweeney.

Re-launch of the Bureau of Lost Causes

The BOLC is back. 10 years ago (in 2010) the Dutch nurse Lucia de Berk was acquitted, at a retrial, of a charge of 7 murders and 3 attempted murders at hospitals in the Hague in a number of years leading up to just a few days before the memorable date of “9-11”. The last murder was supposed to have been committed in the night of September 4, 2001. The next afternoon, hospital authorities reported a series of unexplained deaths to the health inspectorate and to the police. They also put Lucia de B., as she became known in the Dutch media, onto “non-active”. The media reported that about 30 suspicious deaths and resuscitations were being investigated. The hospital authorities not only reported what they believed to be terrible crimes, they also believed that they knew who was the perpetrator.

The wheels of justice turn slowly, so there was a trial and a conviction; an appeal and a retrial and a conviction; finally an appeal to the supreme court. It took till 2006 for the conviction (a life sentence, which in the Netherlands is only terminated when the convict leaves prison in a coffin) to become irrevocable. Only new evidence could overturn it. New scientific interpretations of old evidence is not considered new evidence. There was no new evidence.

Yet already, in 2003-2004, some people with an inside connection to the Juliana Children’s Hospital were already getting very concerned about the case. Having spoken of their concerns, in confidence, with the highest authorities, but being informed that nothing could be done, they started to approach journalists. Slowly but surely the media started getting interested in the case again – the story was not anymore the story of the terrible witch who had murdered babies and old people for no apparent reason whatsoever except for the pleasure in killing, but of an innocent person who was mangled by bad luck, incompetent statistics, and a monstrous bureaucratic system which once in motion could not be stopped.

Among the supporters of Metta de Noo and Ton Derksen were a few professional statisticians, because Lucia’s initial conviction had been based on a faulty statistical analysis of faulty data supplied by the hospital and analysed by amateurs and misunderstood by lawyers. Others were computer scientists, some were civil servants at high levels of several government organs appalled at what they saw going on; there were independent scientists, a few medical specialists, a few persons with some personal connection with Lucia; and friends of such people. Some of us worked quite intensively together and in particular worked on the internet site for Lucia, building an English language version of it, and bringing it to the attention of scientists world-wide. When newspapers like the New York Times and The Guardian started writing about an alleged miscarriage of justice in the Netherlands involving wrongly interpreted statistics, supported by comments from top UK statisticians, the Dutch journalists had news for the Dutch newspapers, and that kind of news certainly got noticed in the corridors of power in the Hague.

Fast forward to 2010, when judges not only pronounced Lucia innocent, but actually stated in court that Lucia together with her colleague nurses had fought with utmost professionality to save the lives of babies which were unnecessarily endangered by medical errors of the medical specialists entrusted with their care. They also mentioned that just because the time of a death of a terminally ill person could not be predicted in advance, it did not mean that it was necessarily unexplainable and hence suspicious.

A few of us, exhilarated by our victory, decided to band together and form some sort of collective which would look at other “lost causes” involving possible miscarriages of justice where science had been misused. Aready, I had turned my own research activities to the burgeoning field of forensic statistics, and already I was deeply involved in the Kevin Sweeney case, and the case of José Booij. Soon we had a web-site and were hard at work, but soon after this, a succession of mishaps occurred. Firstly, Lucia’s hospital paid for an expensive lawyer to put pressure on me on behalf of the chief paediatrician of the Juliana Children’s Hospital. I had namely written some information of some personal nature about this person (who coincidentally was the sister-in-law of Metta de Noo and Ton Derksen) on my home page at the University of Leiden. I felt it was crucially in the public interest to understand how the case against Lucia had started and this certainly had a lot to do with personalities of a few key persons at that hospital. I also wrote to the hospital asking for further data on the deaths and other incidents in the wards where Lucia had worked, in order to complete the professional independent statistical investigation which should have taken place when the case started. I was threatened and intimidated. I found some protection from my own university who actually paid expensive lawyer fees on my behalf. However, my lawyer soon advised me to give way by removing offensive material from internet, since if this went to court, the hospital would most likely win. I would be harming the reputation of rich persons and of a powerful organisation, and I would have to pay for the harm I did. Secondly, on some ordinary internet fora I wrote some sentences defending José Booij, but which pointed a finger of blame at the person who had reported her to the police. That was not a rich person, but certainly a clever person, and they reported me to the police. I became a suspect in a case of alleged slander. Got interviewed by a nice local policeman. And a few months later I got a letter from the local criminal courts saying that if I paid 200 Euro administrative fees, the case would be administratively closed.

This led to the Bureau of Lost Causes shutting down its activities for a while. But it is now time for a come-back, a “re-boot”. In the meantime I did not do nothing, but got involved in half a dozen further cases, learning more and more about law, about forensic statistics, about scientific integrity, about organisations, psychology and social media. The BOLC is back.

ORGANISATION and PLANS

The BOLC has been dormant for a few years, but now that the founder has reached official retirement age, he is “rebooting” the organisation. Richard Gill founded the BOLC on the eve of nurse Lucia de Berk’s acquittal in 2006. A group of friends who had been closely associated with the movement to get Lucia a fair retrial decided that they so enjoyed one another’s company, and had learnt so much from the experience of the past few years, that they wanted to try out their skills on some new cases. We rapidly ran into some serious problems and temporarily closed down our website, though activities continued on several cases, more experience was gained, a lot was learnt.

We feel it is time to try again, having learnt some useful lessons from our failures of the last few years. Here is a rough outline of our plans.

1. Set up a robust formal structure with an executive board (chairman, secretary, treasurer) and an advisory board. Rather than calling it the scientific advisory board as is common in academic organisations, it should be a moral and/or wisdom advisory board, to be kept informed of our activities and to let us know if they think we are going off the rails. 

2. Possibly, make an application to become a foundation (“Stichting”). This means we will also be something like a society or a club, with an annual general meeting. We would have members, who might also like to make donations, since running a web site and occasionally getting into legal trouble costs money.

3. Write about the cases we have been involved in during recent years, in particular: alleged serial killer nurses Ben Geen (UK), Daniela Poggiali (Italy); allegations of scientific misconduct in the case of the PhD thesis of a student of Peter Nijkamp; the case of the AD Herring test and the quality of Dutch New Herring; the case of Kevin Sweeney.

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