The Arbitrary Nature of the Measure

Measurement is completely arbitrary. Without relevant context, any measure is entirely without meaning and just a randomly assigned number.

Here are some examples:

  • The Pint – In the UK a pint is 568ml, whilst in the US it is 473ml.  Meanwhile, if you order a pint of Kingfisher here in India, they will serve you a 330ml bottle.  Pint is just an arbitrary name for something, unless you know the relevant context applied to it in each of these countries, you may get drunk far less quickly than you were expecting.
  • Kilometres per Hour – As far as I’m aware, a km/h is the same in every country of the world, however, your understanding of it will differ based on where you are from and what you are doing.  Every treadmill I’ve been on in my life (which, granted, is not very many) has measured the distance and speed in km/h, despite growing up in a country where miles per hour is the standard currency.  As such, I had reasonably expected the same to be true when I stepped onto a treadmill at a hotel in Madurai (in a country where most things are measured in KM), I merrily set the speed to ’10’ and nearly flew off the back of the bugger – whilst I can do the maths, I don’t instinctively know how fast I can run in mph.  Similarly, I don’t really know how fast an 80 km/h speed limit should feel when I’m driving and whilst I know that a good quick bowler will break the 90mph barrier a few times in an over (sorry Americans, this is a cricket reference) despite living here for 2 years and seeing an awful lot of cricket, 144.84 km/h does not have that same magic ring to it.

Measuring things is actually fairly easy (some things easier than others of course), but that’s only a part of what we have to do as researchers.  It is just as important, if not more so, to place the measures we produce in a context that the audience can understand.

This seems fairly obvious, but it is worth emphasising for two reasons:

  1. The growth of DIY research – I’m confident that most of our smarter clients could construct a questionnaire that would with some success measure the things that they intend it to measure.  It would be far more difficult for them to be able to contextualise the findings in an objective way – either because of bias, inexperience or insufficient information (norms, databases, case histories and so on).
  2. The Methodology Debate – there’s a great post on this over on Katie Harris’ blog, most of which I agree with, but I do believe if we obsess over methodology too much, we run the risk of focusing too tightly on the measures and not enough of what the measures mean.  That’s not to say methodology and rigour where measurement is concerned are not important, of course they are, but at the same time it’s what the measures mean that clients will be interested in.

144.84 kilometres per hour.  Accurately measured via a radar gun.  To me, meaningless.

2 thoughts on “The Arbitrary Nature of the Measure”

  1. Measuring the speed of light also throws up fluctuations that the scientists prefer not to talk about as indeed the do the boiling points of materials which seem to have minute changes which unless ignored create a lot more problems than they solve. Careful of fixed constants.

    1. Which I think actually emphasises why it’s important that we do still talk about methodology and be clear exactly what we’ve measured and how and not hide from what the limitations and level of accuracy of that measurement are.

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