Ross Farrelly

First published in The Canberra Times , 22nd September 2008 One of Kevin Rudd’s favourite mantras is that he wishes to develop “evidence based” policy. That is, he backs policies which have enough supporting evidence to suggest that they will produce their desired effect. However, it is well known in scientific circles that there is one gold standard technique for discovering such a causal relationship between cause and effect– the randomised trial. A randomised trial starts with a hypothesis – a statement of fact which is to be tested in the trial. Stating a hypothesis forces policy makers to move from a vague statements of intent to a specific measurable outcome they wish to achieve. The hypothesis is then tested by randomly selecting two groups of people. One group receives the treatment and one group does not. The power of the randomised trial lies in the fact that the two groups are as alike as possible in every respect except for whether or not they receive the treatment. If afte...

First published,   Policy Magazine , Spring 2008. Policymakers claim to develop programs that will benefit citizens. They claim, either implicitly or explicitly, to have certain knowledge of the causal relationship between the actions they plan to take and the outcomes they wish to achieve. This claim is emphasised when, as Prime Minister Kevin Rudd does so often, they express their wish to develop ‘evidence-based’ policy. It is well known in scientific circles that there is one gold standard technique for discovering such a causal relationship—the randomised trial. If policymakers want to be able to claim that their policies will work, they should subject them to randomised trials beforehand. Randomised trials present the policymaker who genuinely wants to know how to make a difference with a powerful and irrefutable tool to put his or her theories to the test and to draw fact-based conclusions from them.     Randomised trials are the least random and most scientific method known ...

Published - Weekend Australian 5th April 2008. John Naish recommends a data diet to cure us of our addiction to information. I’m been a self imposed diet for quite some time: I have no TV in my house, I’m on to my second master’s degree (which forces me to read books cover to cover and demonstrate that I have comprehended them) and my main source of music is live concerts. This works wonders. My home is a place for the family to bond, not a place to be bombarded by advertising. For entertainment we read, talk and play together. For information we read what we choose. For education we read, study, reflect and discuss. Avoiding infomania is not difficult but you do have to be prepared to be different.

first published in Policy Magazine , Autumn 2008 A review of Super Crunchers by Ian Ayres On a recent visit to my local medical centre I came face to face with the fact that Dr Google now seems to know more than my family GP. I was ushered into the consultation room where I explained my symptoms to a slightly ruffled and obviously overworked doctor. He listened attentively, nodded thoughtfully and then asked for a moment while he entered a few keywords into Google. “Right then,” he continued brightly, “what you have is …” and proceed to diagnose my ailment and prescribe the necessary to clear it up. I was taken aback. What was he doing looking it up on Google? I expected that he’d have enough experience to know what my problem was. And what if the internet was down? Would he just guess? I was reminded of this incident and my reaction to it when reading Super Crunchers . Ian Ayers’ latest book addresses this very question – what is the right use of data and how can conclusions derived ...