Skip to main content

Seduced by Logic – Robyn Arianrhod ***

Though there still aren’t enough women involved in physics, there are certainly are far more than there used to be. When I look back at my 1976, final year undergraduate group photograph at the Cavendish in Cambridge there are probably only around 5 per cent of the students who are female. (It’s a little difficult to tell, given the similarities in hair length favoured at the time.) Now it would be significantly higher. But go back over two centuries and what’s amazing is to find any woman who dared to make herself visible in the scientific arena.
Yet despite the widely voiced concerns that women’s brains would practically explode if faced with anything more than the fluffiest of science popularisation (the father of one of the main characters in this book, discovering her interest in maths, said ‘We must put a stop to this, or we shall have Mary in a straightjacket one of these days’) the two individuals at the heart of Robin Arianrhod’s book managed not just to learn about the physics of the day but to make important contributions.
The first is Émilie du Châtelet. She was worthy of a biography for her life alone, somehow managing despite being married to the aristocratic Marquis du Châtelet, to spend most of her married life in the company of the writer Voltaire (with another lover later on with whom she had a child, though, sadly, Émilie would die shortly after the birth). But she was also a great enthusiast for Newton’s work, doggedly acquired knowledge of mathematics to better her understanding (soon outstripping Voltaire) and writing an influential paper on what we would now think of as energy. Perhaps most remarkably she made what is still the only complete French translation of Newton’s brilliant but often impenetrable masterpiece, the Principia.
Scottish-born Mary Somerville, the second of Arianrhod’s characters, born 70 years later, had more of a middle class background (Arianrhod helpfully puts her on a par in both period and social status with Jane Austen and her principle characters), but still managed to go on to be a world expert on Newton’s work, both providing new insights for the many scientists who struggled with Newton’s sometimes painful obscurity and writing some of the first approachable popular science on the subject. While both woman were of a certain standing, and could not have broken through the way Faraday did from truly humble beginnings, the achievements of this pair when all of society and the scientific establishment was stacked against them was truly remarkable and it is excellent that their work is being detailed here.
Where I have a little concern with the book (as opposed to the subjects) is that Arianrhod sets out to give us too detailed a rendition. Dotting every i and crossing every t of a scientific life is necessary for an academic biography, but here it can get a little plodding at times. It is only because of this that I have not given the book more stars – it is impossible to fault the attention to detail of the biography, nor the interest of the subjects, but the book doesn’t quite have the page turning intensity that these women’s stories could have had with the right approach.
However, if you want to find out more about this remarkable pair of early female Newtonians, this is definitely the book to make you a very happy bunny indeed.

Hardback 

Kindle 
Using these links earns us commission at no cost to you
Review by Brian Clegg

Comments

Popular posts from this blog

Models of the Mind - Grace Lindsay *****

This is a remarkable book. When Ernest Rutherford made his infamous remark about science being either physics or stamp collecting, it was, of course, an exaggeration. Yet it was based on a point - biology in particular was primarily about collecting information on what happened rather than explaining at a fundamental level why it happened. This book shows how biologists, in collaboration with physicists, mathematicians and computer scientists, have moved on the science of the brain to model some of its underlying mechanisms. Grace Lindsay is careful to emphasise the very real difference between physical and biological problems. Most systems studied by physics are a lot simpler than biological systems, making it easier to make effective mathematical and computational models. But despite this, huge progress has been made drawing on tools and techniques developed for physics and computing to get a better picture of the mechanisms of the brain. In the book we see this from two directions

The Ten Equations that Rule the World - David Sumpter ****

David Sumpter makes it clear in this book that a couple of handfuls of equations have a huge influence on our everyday lives. I needed an equation too to give this book a star rating - I’ve never had one where there was such a divergence of feeling about it. I wanted to give it five stars for the exposition of the power and importance of these equations and just two stars for an aspect of the way that Sumpter did it. The fact that the outcome of applying my star balancing equation was four stars emphasises how good the content is. What we have here is ten key equations from applied mathematics. (Strictly, nine, as the tenth isn’t really an equation, it’s the programmer’s favourite ‘If… then…’ - though as a programmer I was always more an ‘If… then… else…’ fan.) Those equations range from the magnificent one behind Bayesian statistics and the predictive power of logistic regression to the method of determining confidence intervals and the kind of influencer matrix so beloved of social m

How to Read Numbers - Tom Chivers and David Chivers *****

This is one of my favourite kinds of book - it takes on the way statistics are presented to us, points out flaws and pitfalls, and gives clear guidance on how to do it better. The Chivers brothers' book isn't particularly new in doing this - for example, Michael Blastland and Andrew Dilnot did something similar in the excellent 2007 title The Tiger that Isn't - but it's good to have an up-to-date take on the subject, and How to Read Numbers gives us both some excellent new examples and highlights errors that are more common now. The relatively slim title (and that's a good thing) takes the reader through a whole host of things that can go wrong. So, for example, they explore the dangers of anecdotal evidence, tell of study samples that are too small or badly selected, explore the easily misunderstood meaning of 'statistical significance', consider confounders, effect size, absolute versus relative risk, rankings, cherry picking and more. This is all done i