Elitism & Science

As the he-said-so-he-must-have-meant pop-psychology goes on over the unexpectedly published EA CRU data, some of the discussion turns to how scientists (or, to be more specific, academic researchers) involved should behave professionally.

We’re all – even most academic researchers – human. We can expect Phil Jones and his team to be angry, to scorn those who question his theories, especially when he sees those theories as vital to the future of humanity. And so he does. So would most of us, though we may be a little more careful about committing those things to email.

Dr Spencer, a well known skeptic, has quite a lot to say about such ‘elitist’ behaviour

Good -isms

But there’s nothing wrong with being elite, with being amongst the best at doing a job. And being able to discriminate on merit – on the ability to do things well – is a vital part of any society that intends to improve its lot.

We similarly must discriminate between ages if we want to avoid sharing a wing with Sidney Cook. We discriminate between religions to book holidays, and when providing meals to guests. We discriminate between sexes if we’re heterosexual, or homosexual. We discriminate between sexual preferences to ensure that those that can’t discriminate between ages get to share a wing with Sidney Cooke. We discriminate again between ages to allow certain ages to get away with not making that discrimination.

And this is all good, if a bit Sir Humphrey.

Bad -isms

But if we consider ‘elitism’ as we consider ‘racism’ (discriminating for differences in behaviour or ability that don’t exist), then we’ve got a much more unpleasant attitude. Then we get people who think that their superior expertise gives them remit to protect that expertise by denying evidence to others, remit to use political or organisation clout to deny them access to publish, or remit to disregard any work by anyone else purely because they are not also ‘officially’ elite.

I’m not convinced however by Spencer’s claim that the CRU team are elitist in that way. Yes they believe themselves right, they believe Spencer and McIntyre and McKintrick and all the other hundreds of skeptical scientists are wrong, and they act as the mini tribe that most of us act when we consider ourselves ‘us’ and others ‘them’. There’s nothing particularly unusual with showing they despise people they think are very wrong and are undermining their hard efforts. Even when it’s rather callous.

And there’s nothing particularly evil about abusive comments from experts about other people’s competence. These are arguments over merit, based on their opinions of each other’s work.

Ordinary tribal -ism.

Declaring that those opinions matter only when they are part of the community is not so good. Apparently they are only worth considering when published in approved journals. Journals that publish them are not approved of, and should be ousted from the community. By somewhat underhand means. Which makes for a nice, comfortable, insular, self-reinforcing community, or ‘ivory tower’ as it is usually known.

So they appear to ‘discriminate against’ McIntyre for example because he’s not part of their community, rather than because he’s not ‘elite’. His theories are ‘discredited’ because they are not published in the community journals, rather than because they are wrong.

He certainly doesn’t fit the community: he publishes openly, on t’interweb, where anyone can and does criticise his work (of course, the CRU community is also now doing this, inadvertantly, and they don’t like it). He has a background in statistics, not environment, and he generally sticks to statistical analysis. And while he’s definitely not an enthusiast for The Cause, he’s careful to remain neutral on what the final conclusion will be.

That Science Thang Agiin.

More importantly than disregarding opinion outside the community (we’re all busy anyway, how much time have we got to consider every criticism everywhere?) or the ordinary abuse and wishful thinking, there are the fairly deliberate discussions about (mis)interpreting the data to fit the cause (eg Bishop Hill, Delingpole – these include some rather dubious criticisms of the emails, but some are very telling).

The complete opposite of the much-vaunted stereotyped scientist that is curious about the differences between theory and observation, and investigates them.

Even so, if these particular twonks demonstrate poor professionalism, bordering and perhaps crossing to deliberate manipulation, misrepresentation and destruction of the data, that only means some of these folks do (some are much better behaved). It would be poor science to infer that’s the case for all climatologists, or reflects on the conclusions of the climatology community as a whole.

Though we might want to check that the wider community is more professional – more scientific – in the same way that we might want to check any other organisation for systematic incompetence when we uncover some in a core part of it.

Anyhow, a few paragraphs from Spencer’s article make much better points about how we outside these academic research communities should view the work that they do:

One of the biggest misconceptions the public has about science is that research is a straightforward process of making measurements, and then seeing whether the data support hypothesis A or B. The truth is that the interpretation of data is seldom that simple.

There are all kinds of subjective decisions that must be made along the way, and the scientist must remain vigilant that he or she is not making those decisions based upon preconceived notions. Data are almost always dirty, with errors of various kinds. Which data will be ignored? Which data will be emphasized? How will the data be processed to tease out the signal we think we see?

Hopefully, the scientist is more interested in discovering how nature really works, rather than twisting the data to support some other agenda. It took me years to develop the discipline to question every research result I got. It is really easy to be wrong in this business, and very difficult to be right.

We can see that we need to do better than ‘hope’, if we are to get any reliable science to inform our votes, lobbying and ‘lifestyles’ on this matter.

Update:Judith Curry (I think this climate researcher), talks about tribalism and the duty of public release here

Hacking: It’s Good for Science

Over the last few days the global warming communities – those ‘for’ and ‘against’ – have been deluged by the news that the computer systems at Hadley’s Climate Research Unit (part of the British Met Office*) have been hacked and the data posted on t’interwebs:

• WUWT: Hadley CRU hacked
• Climate Audit
• Real Climate (staffed by many ‘close’ to the CRU victims)

The alleged docs are here (along with on-line searchable access to the emails) but of course, this is the internet, and you can make up anything you like and post it. (Update: Downloading and expanding it, it appears to include 100mb of uncompressed code and data, mostly tree-ring/bristlecone proxy rather than weather station measurements. If this is made up, then someone’s been very busy; but there is also a danger that it is ‘mostly real’ with some key edits)

Assuming for the moment that these are real, and that Phil Jones does in fact admit it, then this is not good for the reputation of Science-The-Human-Endeavour. The tone and contents of the emails squash any claim that ‘you can trust us, we’re scientists, we’re objective and only interested in the facts’ (but then, we know that humans don’t do science)

It doesn’t even help, much, the scientific debate on global warming. As the above discussions show, the main responses are around dishonesty and legality (which are somewhat open to interpretation), rather than analysing the facts and the data. But then the scientific debate has always been very sparse across this general debate; everyone claims to have science on their side and will point to authority, to motivations, to allegiance, to politics, to vested interests, to the number of people working on it, even to assumed ideologies, in order to bolster that claim, but few will actually discuss the science. Well, the science is difficult OK?

But that will come. After the quote mining and short-term tribalist gloating is over, the Big Win for science is the simple straightforward forced releases of data that so far has been kept hidden, for possibly good but still also hidden commercial reasons (That is, CRU wouldn’t show any evidence for why it should be kept hidden, because they claimed to have lost that evidence).

Real Science – that is, the accumulation of a systematic body of knowledge, rather than the insular world of messy so-called-iterative academic research – requires rigour. It requires openness. It requires criticism, whether deserved or not, to tighten arguments and improve evidence quality, and expose gaps and risks. In other words, it requires independent review, or at the very least the threat of it.

Openness is forced internally in any organisation or project that practices ‘due diligence’. We have seen it introduced to medicine in only the last generation or so; many academic organisations** have been reluctant, slow and late to that particular party, for all kinds of ordinary people and practical reasons.

This hack – an externally forced openness – will not do much good in the short term, especially to those involved. But in the long term, we can hope to see researchers who inform public policy become openly professional – and scientific – throughout their work, because now they know that someone, internal or external, may come along one day soon and let unfriendly people examine it. All of it.

Update:Judith Curry (I think this climate researcher), talks about tribalism and the duty of public release here

—

* I’m not actually clear on the differences in responsibilities and allegiances of the Hadley center, The British Met Office, and East Anglia University’s Climate Research Unit. I don’t think they are either.

** And plenty of private organisations too. I’m just picking on researchers whose work is used to drive public policy (and I’ve made some changes to the text to make this clear)

STAB Stops

Edited from Arrse:

“STAB stabbing OK. STAB stops. Unload. Make STAB Ready. STAB stabbing OK. STAB stops. Unload. Wait 17 years……

STAB fails to load. On closer inspection, TA appears to be shagged. Return STAB to stores until the country unfucks itself.“

I had rather naively assumed that the reason my TA (Territorial Army) unit had cut down on training was because of a local ‘administrative error’, overrunning their budget.

But no, it seems the government/MoD has decided to withdraw funds for training anything except direct operations.

Now, the TA runs, roughly, as a way of drawing on a segment of the population that doesn’t want to make the military a career, but can still contribute to operations. This might be as fill in to fighting forces, or more valuably as specialists such as drivers or medics. With recent long-term large-scale operations, this draw and rotation is quite heavy, but continues to draw those who can and want to contribute but still maintain another, main, career.

People like me

Part time activities create and require commitment. If you can’t practice one activity, you tend to move to something else – and as you do, you commit to them, the social contacts, the skills. The old ones fade. It becomes a hurdle to moving back to the old one when it becomes available again.

This means that when – or if – the TA restarts, there is no core left to pass on not just technical skills but attitudes and experience.

Background training provides a core skillset to launch from for operational training. Years of TA experience do not equate to years of regular training, but are far superior to a few months of pre-deployment training for newcomers.

It’s not as if STABs are useless

And even those who don’t deploy provide people to train with. If, out of any group of TA soldiers, only a few mobilise, the others provide the bulk to run usefully sized exercises; without them you just don’t get the scale of training. Even for those that don’t intend to deploy initially, circumstances change. And they are also available for the more extreme remit of the TA: national emergency.

It might be another training model would work. The pay is an important compensation for the time away from family and friends, but there’s still opportunity for those of us who don’t need that to train. But that’s not the way the organisation is able to operate.

At a stroke, the current government appears to have saved a tiny tiny part of the budget at the expense of mid term capability – capability that the next government will have to cope with. It appears a deliberate act of espionage on not just the next government (Labour must expect to lose the election) but the resources our fighting forces can draw on.

(A more considered post by my old CO)

Fool on 4

File on 4 from the BBC have an episode on military procurement: “Gerry Northam asks why it seems so hard to buy the right equipment for our forces.”

Now there are many many problems with the UK military’s procurement process, and I hope to do a series on it, but this BBC ‘investigation’ completely failed to get past the symptoms, and instead blindly carried on with the short sightedness that drives some of those problems.

False economies of scale

Early on is the assertion that if all the army had the same vehicle, with the same engines and the same spares, think how much easier that would be to manage.

Which is only true in the most simple of ideal worlds: how much easier it would be to maintain computers, or showers, or cars, if they were all the same.

It is true, but it misses some major issues: (1) we want the right kit for the job, not some generic not-quite-good-enough-for-anything (2) circumstances change, and we can’t expect to upgrade everything everywhere all the time and (3) quite apart from anything else, in practice we have to buy what we can get, and that might mean buying some Jackals, some Panthers and some Mastiffs (or Cougars – what is it with the predatory animals?)

That means we will have different kit in different places, some of it rightly modified by local engineers to fit the local problems. Trying to enforce some centrally dictated and lengthy equipment procurement diverts effort from developing systems to support the real world, and even undermines them.

Soldiers are at put at risk because of…

The piece leaned heavily on soldiers who had been killed “due to” some problems with the equipment, leaving interviewees to try and start from scratch to explain problems with such a single-minded approach.

Soldiers – like many other professions – work in an inherently risky environment, and any who die can be used as an argument that better armour, better firepower, better gadgetry, better speed, better communication, better transport and so on might have saved their lives, while completely ignoring any of the costs that arrive with those improvements. Such as the problems of having more armour on the mobility or reliability of a vehicle.

Most decisions made by high level management are going to result in the deaths of soldiers in a warfighting environment; the costs must be balanced with the effects required. For example recently efforts are going into clearing houses by hand, rather than by dropping large explosives on them, thus preserving the property and shelter of local civilians. This results in more immediate risk and so more soldier deaths, but with the intended benefit of longer term peace. Any reporter criticising it with only “Soldiers die because of this!!!” should be ignored for extreme naivity.

The Vector’s failing wheel hubs

Gerry is quite right to point out the failing points of the Vector (generally the wheel hubs that failed under the weight of the armour and the ground conditions) but then falls apart when doesn’t think through his follow on questions: “Did nobody think of it?” as if somehow hindsight should have been obvious in forsight.

Testing and evaluating the complete drivetrain of a vehicle for a variety of terrains and loads is not a ten minute job, and takes many months at best. If demands change then the vehicle would need to be re-tested and might never leave the testing ground.

Which is the main point missed; Gerry compares the failing Vectra with some mythical perfect vehicle, not the real world alternative: the Snatch Land Rovers (or indeed on the fairly bog standard unarmoured Land Rovers and Bedfords we had). The military bought Vectors because they needed something quickly, and they got it. It wasn’t right, but it was better than what they had, and when they failed the military resorted to the Land Rovers – until the better Mastiff turned up. A more interesting (but still hopelessly naive) question, might be: “Why didn’t they already have the perfect vehicle before we went to war?”

The top-heavy Puma

Again, the complaints are that there is something wrong with the existing kit, and how it should not be in service because it’s not right. Which would mean that more time should be spent developing equipment to a high level of safety, and while that is happening the troops have to wait.

The Mastiff Supply Chain

We get a little closer to interesting supply chain problems with the Mastiff, which had axle failures, and replacements were not available as the manufacturer’s priority was the American Army it was supplying as well, not the British.

Get me it now. And get me the fixes soon after

Programmes like these increase the political pressure for zero-risk purchases.

We should (in my obviously very humble yet quite right view, ahem) be looking at ways of informing those who need the equipment (the soldiers) with the problems in establishing supply chains, rather than trying to train more remote desk-bound procurement beaurocrats with what is required on the front line. With that is the key requirement that changes can be made; adaptations to the deployed equipment and new equipment quickly brought in to fill gaps or failures.

When there is no evidence

or “Now where did I leave my glasses?”

An engineer, a mathematician and a physicist look out of a window of a train passing through the highlands of Scotland, and see a black sheep.

“Ah!”, says the engineer, “Look, they have sheep in Scotland!”.

The physicist looks at it and reflects “Well, we can say only there is at least one black sheep in Scotland”.

The mathematician looks at them both in surprise “That’s not right at all! All we can tell is that one side of one sheep in Scotland is black”

Ho. Ho.

This is one in a series of posts , about evidence and how it does or does not support a claim.

Such pedantry is over the top, but it serves to illustrate a simple point about what we can really infer from a piece of evidence, and its limitations.

It’s easy to decide what to believe when you have clear positive evidence in your hand: the photo of your girlfriend in bed with that sysadmin from finance is fairly firm (heh) evidence of her faithlessness.

It’s not so clear when there is no evidence for something, and interestingly there is more than one way in which we can not have evidence for something.

‘Bounding’ what we don’t know

Those who are old enough will know what it’s like: we lose our reading glasses, or the screwdriver, or pen or mug of tea we had in hand only a few minutes ago.

At this stage, if somebody rather stupidly asks “Well where did you leave them?” we would rightly and angrily reply “I don’t know, if I knew where they were, I wouldn’t have lost them”.

So we don’t know where they are, but we do know some places where they are not. They are not on Mars. And although we may not remember all the rooms we’ve been to since we last remember having them, we tend to remember unusual places; mine are not, for example, in the attic as I know I haven’t been there.

This gives us some limits, some ‘boundaries’, to the area of ignorance.

Reducing the area of ignorance

As we start to look we start to limit these boundaries further.

A quick walk around the usual rooms glancing at the surfaces for example is a good first stage search; it covers a lot of ground for a fairly likely result.

By discounting the places we’ve looked – and by starting with the most likely and easily surveyed places – we reduce the places the glasses could be.

“Knowing it is not” is not “Not Knowing”

Having thoroughly searched the mostly empty fridge, I know to a high degree of confidence that my glasses are not in there.

I have no evidence of that, and I have no proof that they are not (I may have forgotten to search the bowl of three week old leftover gravy) but my memories of looking are ‘evidence of no glasses in the fridge’ (‘evidence of lack’) rather than ‘no evidence of glasses in the fridge’ (‘lack of evidence’).

The latter though is still how you might reply to “Are they in the fridge?”, even though it doesn’t capture whether you’ve looked or not.

This causes problems when people want to know if there’s any danger in some treatment or chemical. To be told “There is no evidence of any harm” is useless; it doesn’t tell us if nobody’s checked, or if they’ve had a quick look and everything seems fine, or they’ve had a really very thorough search that would have turned up any significant harm and found nothing.

What we think we don’t know

So I continue with my exercise in limiting my ignorance, hoping one day to find my glasses so that I can carry on doing what I was doing… whatever that was… it will come to me in a moment… and sometimes we get a bit irrational. How many times, frustrated, have we looked in the same box, under the same small piece of paper that couldn’t possibly hide a pair of glasses?

Similarly our boundary reducing exercise is not ‘certain’; it may be I’ve looked somewhere but not seen them (after all, I’m not wearing my glasses). It may be I’ve looked in an area where they are hidden, and have declared and marked the whole area ‘glasses free’ when in fact it is not.

In more general terms, not finding doesn’t necessarily mean it’s not there: just because all the swans I’ve seen are white, does not mean there are no black swans.

This is where we reach the limits of our understanding of our limits of our ignorance. We rarely properly match the boundaries of what we think we don’t know with what we actually don’t know.

This gap is where my lost glasses still lurk when I give up and use an old pair: in the world of places I haven’t looked well enough, but can’t think of to look.

Theories of what might be

I was slightly too certain above about where my glasses are not, as aliens might have stolen them and taken them to the Mars.

And if we return to the railway carriage with the sheep-observing pedants, we might claim that “There are luminous pink sheep in Scotland with legs on one side shorter than the other. Scostmen hunt them down and turn them into haggis and bagpipes”.

We can make up any silly story we like (“Aliens live in clouds!” “Pixies ate my hamster!” “Magnets healed my cancer!” “Hair loss makes you sexy!”) and some may be accidentally true but it’s no more sensible to assume they are true without evidence than it is to believe in Garibaldi Mountain Shrews.

Not knowing something is no excuse to make up any old thing and then believe it to be true, any more than it is to believe that your glasses are in the kitchen, because you don’t know where they are, and they could be.

This is the ‘out’ for a lot of so-called ‘open minded’ views: “Just because you haven’t seen pixies, you must be close-minded to disbelieve them”.

Pixies might exist, this is true.

But when you consider all the things that might exist, such as invisible baby-eating multi-coloured pixie-swans that live with aliens in clouds, then you can see that believing in any random made up fantasy can be fun but it’s not very practical.

If someone tells you some far fetched story and says “well, you’ve got no evidence against it, so it could be true couldn’t it?” then the answer is “yes, and aliens are painting your ears”

“I don’t know”

A straightforward ‘we don’t know’ seems a bit of a cop out, and the mind abhors a vacuum, but this is no excuse to fill it with speculation and then infer ‘truths’ from them. (It’s fine to speculate and test: Perhaps the glasses are in the bathroom? I shall go and look)

Even if you’ve only ever seen white swans, you can’t be sure that all swans are white. You just might not have seen one that isn’t.

Yet lack of evidence is not evidence of lack; just because we haven’t seen something doesn’t mean it’s not there.

It’s alright to say we don’t know. It’s alright to say we think things are likely, or unlikely, but we’re not sure. And working out what we don’t know – or what exactly we’re not sure about – tells us a very valuable thing: what we still need to find out in order to know.

Background evidence

The above of course is a bit “simple”. It ignores all the background evidence we hold; there are very few sheep with black on one side and white on the other, so we can happily infer that a sheep is black from seeing the one side of it that is. This is material for another post…