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Macabre Tales From Dystopian Britain

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Evidence in support of UK DNA database is "most unclear and badly presented piece of research"

The British Home Office want to keep a huge DNA database of people who've been acquitted of crimes (or arrested and then released with charges dropped), saying that "innocent people who have been arrested are as likely to commit crimes in the future as guilty people." In support of this "controversial assertion" they cite a piece of research that Guardian science columnist Ben Goldacre calls "possibly the most unclear and badly presented piece of research I have ever seen."

On page 30 they explain their methods, haphazardly, scattered about in the text. They describe some people "sampled on 1st June 2004, 1st June 2005 and 1st June 2006". These dates are never mentioned again. I have no idea what their plan was there. They then leap to talking about Table 2. This contains data on people each from a "sample" in 1996, 1995, and 1994, followed up for 30 months, 42 months, and 54 months respectively. Are these anything to do with the people from 2004, 2005, and 2006? I have no idea.

In fact I have no idea what "sample" means, perhaps that was the date they were first arrested. I don't know why they were only followed up for 30, 42, and 54 months, instead of all the way to 2009. Crucially I also don't know what the numbers in the table mean, because they don't explain this properly. I think it is the number of people, from the original group, who have subsequently been arrested again.

Anyway. Then they start to discuss the results from this table. They say that these figures show that arrested non-convicted people are the same as convicted people. There are no statistics conducted on these figures, so there is absolutely no indication of how wide the error margins are, and whether these are chance findings. To give you a hint about the impact of noise on their data, more people are subsequently re-arrested over the 42 month period than over the 54 month period, which seems surprising, given that the people in the 54 month group had a much longer period of time over which to get arrested.

Is this a joke?

We’d all like to help the police to do their job well. They, in turn, would like to have a massive database with DNA profiles from everyone who has been arrested, but not convicted of a crime.

We worry that this is intrusive, but some of us are willing to make concessions, on our principles, and the invasion into our privacy, in the name of preventing crimes. To do this, we’d like to know the evidence on whether this database is helpful, to help us make an informed decision.

Luckily the Home Office have now published a consultation paper on the subject. They defend their database by arguing that innocent people who have been arrested are as likely to commit crimes in the future as guilty people. “Thisâ€, they say, “is obviously a controversial assertionâ€. That’s not true: it’s a simple matter of fact, and you could easily assemble some good quality evidence to see if it’s true or not.

The Home Office have assembled some evidence. It is not good quality. In fact, this study from the Jill Dando Institute, attached to their consultation paper as an appendix, is possibly the most unclear and badly presented piece of research I have ever seen in a professional environment. Or I am having a bad day. Join me in my struggle to understand their work.

They want to show that the level of criminal activity in a group of people who have been arrested, but on whom no further action has been taken, is the same as the level of criminal activity in people who have been arrested and convicted of a crime, or who accept a caution.

On page 30 they explain their methods, haphazardly, scattered about in the text. They describe some people “sampled on 1st June 2004, 1st June 2005 and 1st June 2006â€. These dates are never mentioned again. I have no idea what their plan was there. They then leap to talking about Table 2. This contains data on people each from a “sample†in 1996, 1995, and 1994, followed up for 30 months, 42 months, and 54 months respectively. Are these anything to do with the people from 2004, 2005, and 2006? I have no idea.

In fact I have no idea what “sample†means, perhaps that was the date they were first arrested. I don’t know why they were only followed up for 30, 42, and 54 months, instead of all the way to 2009. Crucially I also don’t know what the numbers in the table mean, because they don’t explain this properly. I think it is the number of people, from the original group, who have subsequently been arrested again.

Anyway. Then they start to discuss the results from this table. They say that these figures show that arrested non-convicted people are the same as convicted people. There are no statistics conducted on these figures, so there is absolutely no indication of how wide the error margins are, and whether these are chance findings. To give you a hint about the impact of noise on their data, more people are subsequently re-arrested over the 42 month period than over the 54 month period, which seems surprising, given that the people in the 54 month group had a much longer period of time over which to get arrested.

This is before we even get on to the other problems. At a few hundred people, this study seems pretty small for one that is supposed to give compelling evidence that there is no difference between two groups, because to prove a negative like this, you’d generally want a large sample, to minimise the chance of missing a true difference in the noise.

There is no evidence that they have done a “power calculation†to determine the sample size they’d need, and in any case, their comparison group feels a bit rigged to me. In their “convicted†sample they only count people who had a non-custodial sentence, and exclude people who got a custodial sentence, on the grounds that those people would be incapable of committing a crime during their incarceration. This also has the effect, however, of making the “criminal†group not quite so criminal, and so a bit more likely to be similar to innocent people.

I could go on. Table 1 is so thoroughly “not as described†as to be uninterpretible. In the text they talk about different cells on the table which are “solid redâ€, “stippled yellowâ€, and “blankâ€. In fact the whole thing is just blue.

This research was incomprehensible and unreadable. Anybody who claims to have been persuaded by the data quoted here is telling you, loudly and clearly in the subtitles, that they don’t need to understand a piece of research in order to find it compelling. Such people are not to be trusted, and if research of this callibre is what guides our policy on huge intrusions into the personal privacy of millions of innocent people, then they might as well be channeling spirits.

And a case of the state peeing in your face...

UK National Portrait Gallery threatens Wikipedia over scans of its public domain art

Britain's National Portrait Gallery is threatening to sue Wikipedia for including some of its high-rez scans of public domain portraits. In Britain, copyright law apparently gives a new copyright to someone who produces an image full of public domain material, effectively creating perpetual copyright for a museum that owns the original image, since they can decide who gets to copy it and then set terms on those copies that prevent them being treated as public domain.

The NPG, whose budget is almost entirely derived from public funds, supplements its income by licensing photos of its paintings to books and for the web. They are so protective of this small bit of income that they even prohibit photographs of their "no photography" signs (they argue that these signs are copyrighted).

They argue that they can service the public -- whose taxes sustain them -- by extracting additional rents from photos instead of seeing to it that they are widely distributed. This is an increasingly common argument by public institutions, for example, the BBC jealously guards its additional DVD income and shies away from any kind of public archive that might undermine it, saying that the five percent of its budget derived from commercial operations is so important that the material funded with the other 95 percent of its income -- which comes directly from the public -- should be locked up.

At the end of the day, you either buy this argument or you don't. I don't. If you take public money to buy art, you should make that art available to the public using the best, most efficient means possible. If you believe the public wants to subsidize the creation of commercial art-books, then get out of the art-gallery business, start a publisher and hit the government up for some free tax-money.

I don't really think that this has anything to do with income. I think it's the NPG's ingrained philosophical approach. A couple years ago, they had a show of pop-art portraits by the likes of Warhol, et al, and practically every single portrait represented some kind of copyright infringement. Seemingly without irony, the NPG prohibited photos of these infringing works "to protect their copyright." At the time, I asked whether they were celebrating the creativity of the pop arts, or eulogizing it. Today's Warhols have no friends at the NPG, who are only interested in celebrating fair dealing if it took place 30 years ago.

"It is hard to see a plausible argument that excluding public domain content from a free, non-profit encyclopaedia serves any public interest whatsoever," he wrote.

He points out that two German photographic archives donated 350,000 copyrighted images for use on Wikipedia, and other institutions in the United States and the UK have seen benefits in making material available for use.

Another Wikipedia volunteer David Gerard has blogged about the row, claiming that the National Portrait Gallery makes only £10-15,000 a year from web licensing, less than it makes "selling food in the cafe".

Leave us lone.

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As a slight aside,

if you haven't read Ben Goldacre's 'Bad Science', I would recommend that you clear a weekend, get plenty of coffee/tea & hobnobs/jaffa cakes in and read it cover to cover.

When you surface you will be laughing hysterically and despairing at the general stupidity he points out.

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I feel your pain. When you think about it the quality of research, analysis (and literacy) on HPC can be equally poor on occasion. I'm sure you can think of some examples.

The solution is the same whatever the source, read the sources,cross-check where possible, quality check the analysis, make up your own mind about the conclusions, and don't assume what people say is accurate or well thought out.

For example; Just because a web site says something is wrong don't assume its correct. I suspect the National Portrait Gallery have a good case and the wikipedia chap was at best disingenuous - what did to get hold of and process the images is hardly consistent with them being public. I predict the parties will come to some agreement, the high-res images will be removed from Wikipedia and lower resolution ones might be offered instead - as other galleries have done.

Generally when something is poorly written up it may not mean the underlying research invalid. The fault lies with the editor and peer reviewers of the publication in which it appeared. (It having been my task to peer review on occasions I can promise you that poorly written pieces of work are not unusual nowadays. The trick is to advise the author and have them revise their paper.)

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