A new study has estimated that over 500 Tamils were forcibly disappeared in just three days, after surrendering to the Sri Lankan army in May 2009.

The study, carried out by the Human Rights Data Analysis Group and the International Truth and Justice Project, based on compiled lists which identify those who were known to have surrendered, estimated that 503 people had been forcibly disappeared between the 17^th– 19^th of May 2009.

The Sri Lankan army must explain to the families of the disappeared and missing what happened to an estimated 500 Tamils who disappeared in their custody at the war end on/around 18 May 2009, said two international NGOs who have been collating and analysing lists of names.

Sri Lanka has one of the largest numbers in the world of enforced disappearances but these 500 represent the largest number of disappearances all in one place and time in the country. For a detailed account of the process of estimating the 500 please see: “How many people disappeared on 17-19 May 2009 in Sri Lanka?” .

From the article: “Based on Ball’s calculations, using our data, nearly 3,000 people could have been killed in the three areas we analyzed in the first 18 months of the drug war. That is more than three times the official police count.”

Earlier this year, the Canadian Tamil Congress connected with HRDAG to bring its campaign to Toronto’s annual Tamil Fest, one of the largest gatherings of Canada’s Sri Lankan diaspora.

Ravichandradeva, along with a few other volunteers, spent the weekend speaking with festival-goers in Scarborough about the project and encouraging them to come forward with information about deceased or missing loved ones and friends.

“The idea is to collect thorough, scientifically rigorous numbers on the total casualties in the war and present them as a non-partisan, independent organization,” said Michelle Dukich, a data consultant with HRDAG.

Ball analyzed the data reporters had collected from a variety of sources – including on-the-ground interviews, police records, and human rights groups – and used a statistical technique called multiple systems estimation to roughly calculate the number of unreported deaths in three areas of the capital city Manila.

The team discovered that the number of drug-related killings was much higher than police had reported. The journalists, who published their findings last month in The Atlantic, documented 2,320 drug-linked killings over an 18-month period, approximately 1,400 more than the official number. Ball’s statistical analysis, which estimated the number of killings the reporters hadn’t heard about, found that close to 3,000 people could have been killed – more than three times the police figure.

Ball said there are both moral and technical reasons for making sure everyone who has been killed in mass violence is counted.

“The moral reason is because everyone who has been murdered should be remembered,” he said. “A terrible thing happened to them and we have an obligation as a society to justice and to dignity to remember them.”

From the article: “Intentionally inconsistent tracking can also influence the final tally, notes Megan Price, a statistician at the Human Rights Data Analysis Group. During the Iraq War, for example, officials worked to conceal mortality or to cherry pick existing data to steer the political narrative. While wars are handled differently from pandemics, Price thinks the COVID-19 data could still be at risk of this kind of manipulation.”

“In 2016, two researchers, the statistician Kristian Lum and the political scientist William Isaac, set out to measure the bias in predictive policing algorithms. They chose as their example a program called PredPol.  … Lum and Isaac faced a conundrum: if official data on crimes is biased, how can you test a crime prediction model? To solve this technique, they turned to a technique used in statistics and machine learning called the synthetic population.”

“In a recent article, social scientist Patrick Ball revisited his and Kristian Lum’s 2015 study, which made a compelling argument for the underreporting of lethal police shootings by the Bureau of Justice Statistics (BJS). Lum and Ball’s study may be old, but it bears revisiting amid debates over the American police system — debates that have featured plenty of data on the excessive use of police force. It is a useful reminder that many of the facts and figures we rely on require further verification.”

William Isaac is quoted.

HRDAG director of research Patrick Ball is quoted in this New York Times article about a paper that models death tolls in Gaza.

When Patrick Ball was introduced to Ibero’s database, the director of research at the Human Rights Data Analysis Group in San Francisco, California, saw an opportunity to turn the data into a predictive model. Ball, who has used similar models to document human rights violations from Syria to Guatemala, soon invited Data Cívica, a Mexico City–based nonprofit that creates tools for analyzing data, to join the project.

“Every kind of classification system – human or machine – has several kinds of errors it might make,” [Patrick Ball] says. “To frame that in a machine learning context, what kind of error do we want the machine to make?” HRDAG’s work on predictive policing shows that “predictive policing” finds patterns in police records, not patterns in occurrence of crime.

Kristian Lum discusses the challenges of getting accurate data from conflict zones, as well as her concerns about predictive policing if law enforcement gets it wrong.