Generalising

Via Andrew Garrett, this amusing image: two signs, one advertising a $50 reward for a lost ipod… and the other advertising a $51 reward for a lost ipod. Amusing, but I can’t see anyone actually calling the $51 guy.

Let’s assume you were indeed some kind of conniving scammer; how would you go about this, presuming that “take down the first poster” isn’t an option? The person who lists second needs to pick a value that increases the plausibility of their poster (is a round number) and provides an economic incentive to call them (is larger) without being self-defeating (is too expensive compared to just buying one).

If the poster had said $60, we might have taken it more seriously – it’s a round number, so it looks more independently plausible – but this doesn’t automatically make it more convincing than the first. When you’re approaching the two signs with the knowledge that one of them is a scam, you’re thinking more critically than usual, and so you’re trying to deduce which one is legitimate.

Seeing the two signs, you’re likely to run through something like the above chain of logic and conclude – one of these two is a scammer, and it makes sense that it’s the higher one. Would it, then, be smarter to deliberately flout the economic aspect and undercut the legitimate poster? Your price is the only way of signalling your plausibility you have, and a lower price implies that you were first to advertise – because it’s irrational to make a lower bid after a higher one.

There is a counterargument that most finders wouldn’t be this honest – they would be motivated by nice simple economic motives first, and so would call the person offering an extra $10. But this doesn’t really reflect the situation: we know that the market value of a second-hand ipod must be more than the amount the scammer offers as a reward, and so a large number of those motivated by purely economic motives would no doubt want to sell the ipod (or keep it). If someone is already contemplating the reward posters at all, they’ve indicated a willingness to take a nominal loss in the interests of “justice” by returning it to its owner.

Alternatively, I suppose, you could counterbid $50, thus anulling pretty much any benefit either you or the original poster would have and turning it into a game of chance. Which offers better odds?

I wonder what we’d get from testing this… is there a sweet spot, just above or just below the original reward, where you’re most likely to get a response?

Mike Peel of WMUK points out the new governmental policy on public archives. A couple of interesting figures to highlight:

• There are about 300 publicly funded archives; half local government, a quarter universities, then museums etc making up the remaining third.
• Per-capita funding for archive services by local government varies by a factor of twenty-two between the best and least funded regions. (In absolute terms, which is a bit less meaningful due to sharp population distinctions, it’s a factor of forty)
• Less than 50% of material is described in online catalogues; less than 1% is accessible via digitisation programs. (I suspect the missing word there is vastly less than 1%…) [p. 14]
• The National Archives provides 170 digital documents for every one used in a reading room, and given the overall figures (112m) that suggests a reading-room usage of 650,000 per year. [p.18]

One figure that would have been very helpful would be an estimate – even an order-of-magnitude ballpark estimate – as to the economic value of public archives. Section 2 talks at some length about the tangible benefits of archives, and indeed mentions economic benefits twice alongside things such as supporting public decision-making or academic research, but the whole section is quite vague and devoid of numbers to quantify what those economic benefits are.

Whatever the plan that follows this report turns out to be, it’ll imply government spending in some way or another; to help make the case for supporting these services properly we need to be able to say – archives are [potentially] worth fifty million to the country a year, or a hundred million, or whatever number it might be. People make these numbers for libraries, for museums, for school playing fields… it shouldn’t be too difficult for the sector to say, upfront, this is what we’re worth to you, treat us accordingly.

(It may seem a bit blunt – but, well, arguing for more public funding without hard numbers is like going unarmed to a duel. You may go through all the motions, but unless your opponent is very scrupulous, you’ll lose)

An interesting new project: Where Does My Money Go? [currently an alpha version; details; announcement]

Basically, interactive visualisations of UK governmental spending, broken down by topic or by region. There’s also a time-series function, which is quite interesting to see – overall government spending, as a proportion of GDP, has just hit the bad old days of 1992.

Things that currently stand out as major issues:

• uncleaned data means hideous governmental terminology – “n.e.c.” everywhere
• expanding on that, the data needs a bit more organising – ensuring you can switch between subdivisions on the national-level, for example, would mean linking the ‘economic > transport’ sections together in the same way that the ‘economic’ sections currently are
• the main charts are a little ambiguous as to which circles are subdivisions of each other
• there’s no way to apply the time-series graph to “second level” data – so you can compare “general public services” spending over time, but you can’t compare the amount spent on debt servicing
• mousing over a column really should display its numeric value

On the whole, though, promising – definitely worth ten minutes playing with. Gets the concept across a lot more clearly than the bare figures might.