Book reviews by SRA members

Reflexivity: the essential guide
Tim May and Beth Perry
SAGE Publishing, 2017

Reviewed by Dr. Oliver Hooper, School of Sport, Exercise and Health Sciences, Loughborough University

Just as it says, this essential guide provides a thorough outline and analysis of reflexivity, the critical examination of how we see the world. It comprehensively traces the history of the concept, and in doing so, presents a host of influential thinkers and their key ideas on reflexivity. The book is written in an accessible style and communicates complex concepts in a way that is relatively easy to understand. The structure of the book is interesting, in that the chapters seemingly operate in pairs. For example, through chapters 3 and 4 the different forms of reason are explored. The advantage of such a structure is that the chapters are kept to a readable length, but not at the expense of detail. The use of ‘learning boxes’ also enables key concepts and issues to be discussed in detail, further enhancing the reader’s knowledge and understanding, without detracting from the main narrative of the chapter.

The book will appeal to a broad readership, from novices to experienced researchers, though would likely be particularly useful for those studying within the social sciences and seeking a better grasp of the concept of reflexivity. The book draws on examples from a range of disciplines within the social sciences, and while this makes it relevant to a broad readership, some readers may struggle to engage with examples that are not relevant to their particular discipline.

Overall, though, the book is a useful read for anyone engaging in social research: a lot of ground is covered in a rather concise text. It not only provides the reader with knowledge and understanding of reflexivity from a theoretical perspective but also supports them to apply it practically within their research. A highly recommended read!

Classic grounded theory
Judith A. Holton and Isabelle Walsh
SAGE Publishing, 2017

Reviewed by Catharine Rose, director, Tiller Research Ltd

This accessible and succinct book contains a wealth of theoretical and practical information which will interest those new to grounded theory, and those already familiar with this approach. The first chapters provide a useful overview of the development of grounded theory by sociologists Glaser and Strauss, describing the fundamental ‘pillars’ of a classic grounded theory approach. The authors then offer a practical, comprehensive account of how to undertake a grounded theory study covering data collection and data analysis methods. The authors explain the importance of generating theory from the analysis, fully describing how this process can be undertaken. They provide considerable practical detail on key techniques such as coding, memo-writing, constant comparative analysis, and how to work with the traditional paper-based sorting methods. However, there is limited guidance on the use of qualitative analysis computer software, which is a pity given the increasing popularity of these programmes. The final chapters discuss both how to write up and how to evaluate a grounded theory study, with a focus on scholarly writing.

The emphasis throughout is on understanding the method and staying true to the underpinning philosophy of grounded theory, while applying this in practice to generate quality results. Appendices give examples of grounded theory from the authors’ own work, and other useful reference material. As a mixed methods researcher, I found the example of combining qualitative and quantitative data in a grounded theory study particularly interesting, having previously only seen the method applied to qualitative data.

In short, this is a useful book for anyone wishing to gain a richer understanding of grounded theory. The practical guidance given by the authors enables researchers to firmly anchor their work in the principles of classic grounded theory, while flexibly and creatively applying the method in their own work.

Social policy in times of austerity
Kevin Farnsworth and Zoe Irving (eds)
Policy Press, 2015

Reviewed by Dr Yoric Irving-Clarke, independent scholar

This book provides an academic discussion of the development (or retrenchment) of government spending since the financial crisis of 2008 and, in particular, since the election of the Conservative/Liberal Democrat coalition government in 2010. It covers the period up to the election of the Conservative government in 2015. The book conceptualises ‘austerity’ as a retrenchment in government spending on social security policies as a response to the 2008 financial crisis, and the use of the crisis as justification to shrink welfare provision across the developed world.

As an edited volume, the book draws upon experts in several fields to make the case that austerity, as defined above, is taking place, and to suggest some alternative policy prescriptions to redress the financial crisis. The historical focus in Michael Hill’s chapter is a welcome addition as this is a perspective that is often ignored in such discussions. Hill’s chapter provides a strong analysis of how not only economics, but also politics, have influenced policy since the 1920s. Throughout the various chapters, the authors make both a moral and an economic case against ‘austerity’ policies and the retrenchment of ‘welfare states’ across the developed world.

At times, the book can fall into the trap of advocating increasing government spending as a ‘Keynesian’ response to recession, ignoring the fact that Keynes advocated a counter-cyclical approach to government spending rather than merely increasing spending at times of economic crisis. Also, to my mind, it does not address globalisation and the wider effects this has had economically or politically.

Nevertheless, this is a timely and thought-provoking collection of essays which will help scholars of social policy to make sense of the deep changes seen in welfare and other spending in recent years. Overall, this book is to be recommended to both scholars and anyone else with an interest in the area.

An introduction to secondary data analysis with IBM SPSS statistics
John MacInnes
SAGE Publishing, 2016

Reviewed by Dr Janet C. Bowstead, Royal Holloway, University of London

This is an excellent guide to the ever-growing amount of easily accessible data available for analysis on social science topics. The author argues that the basis of social sciences as sciences is their approach to empirical evidence, and the first chapter is an overview of the opportunities and limitations of secondary data analysis. The book provides a good grounding in statistics, before going on to explore secondary data analysis specifically. This provides both a useful reference chapter to return to, and ensures that readers revise the basics before leaping into the data. The book is written in an accessible and practical style, and is accompanied by a comprehensive website, so that it could be used both for individual study and for group teaching. Frequent screen-shots of SPSS ensure that the analysis can be followed using either syntax or menus and icons (Graphical User Interface), and there are handy hints to help you keep track of your data analysis and presentation.

As a researcher who has worked with administrative as well as survey data, I think that the book is realistic in emphasising the importance of both extensive data preparation and the development of consistent data management practices before any actual analysis is possible. Sometimes the analysis is the easy bit! The case studies in the book include examples of European and US datasets, as well as data downloaded using the UK Data Service, thereby illustrating the accessibility of such social survey data to students as well as researchers. A particularly interesting feature is the examples which attempt to replicate published academic papers. Such analysis develops both data-analysis and critical thinking skills, as readers are encouraged to engage with, and question, published social science research.

Overall, the book is clear and enthusiastic about statistical analysis of data, whilst never forgetting the social construction of data, or that statistical analysis is a means to an end: ‘good statistics tell a sound story’.

Excel statistics: a quick guide
Neil J. Salkind
SAGE Publishing, 2016 (3rd edition)

Reviewed by Ed Mortimer, programme head, The Nuffield Foundation

There are several specialist statistical analysis software packages available to social researchers – SPSS, SAS, Stata, R, Minitab, among others. This book is aimed at those who do not have access to these packages, and focuses instead on enabling those with access to the Excel spreadsheet software to carry out many of the most commonly used analyses.

While Excel has a large number of statistical functions, the usability and accessibility of these functions are not always simple nor intuitive. Neil Salkind tries to put this right. The book begins with a short, but helpful, introduction on how to use it and two tables, new to this edition, that guide the user on ‘what to use when’, and ‘what you want to find out’. This helps users to understand what they need, and also to be clear about what is (and is, therefore, not) covered. The statistical functions include computing different averages, variability, describing data, correlations and variance, and independence and significance tests.

Each of 40 individual functions is set out clearly in part one, with a brief explanation of what it does, how to use it and an example. There are then a couple of short optional exercises for readers to check their understanding, with answers in the back.

Part two covers the Analysis ToolPak. The tools here (for example on descriptive statistics, sampling, z-tests, t-tests, ANOVA, correlation and regression) combine processes that might require multiple stages using the usual formulae. Again, the format sets out the purpose of the tool and how to use it, and provides an example of output.

Each of the functions and tools covered in Excel Statistics is also included in an accompanying Excel file which is free to download.

Excel is not likely to match, anytime soon, the main statistical packages for analytical power and ease of use. But Excel is much more widely available, and most users don’t get beyond simple formulae in spreadsheets. This volume helps students and analysts to make much better use of Excel’s capabilities to carry out a range of statistical approaches, focusing on what to use, when to use it, how to use it and what the output looks like. Sometimes you just need to make better use of the tools you have at your disposal, and this book will help users do exactly that.

Interpreting qualitative data
David Silverman
SAGE Publishing, 2015, (5th edition)

Reviewed by Rebekah Carney, Faculty of Biology, Medicine and Health, University of Manchester

The 5th edition of Silverman’s ‘Interpreting Qualitative Data’ presents a clear and concise summary of qualitative research. This edition advances on previous editions, including new information on the number of cases needed for a study, including current examples, conducting online research and the wider application to different disciplines. Silverman uses a clear writing style, and manages to explain relatively complex methodologies and concepts in a simple way to the reader, making this book accessible to all.

This book is not just a text book: the additional materials which accompany the book ensure Silverman goes above and beyond simply describing how to interpret qualitative data. The companion website is full of useful additional guidance and resources. Up-to-date case studies are presented throughout, which allow the reader to apply abstract concepts and methods to real-life settings. By presenting examples and short practice exercises within each chapter, Silverman ensures the reader is guided through the process of interpreting qualitative data, and enables an in-depth, hands-on approach to learning.

Each chapter can stand alone, and provides a thorough explanation of everything you need to know to conduct a qualitative analysis. Furthermore, the examples used throughout show how this book can be used across a range of disciplines such as psychology, sociology, health, humanities and medical research.

A particularly valuable addition to this edition of the textbook is the chapter on conducting qualitative research online and ethics of doing internet research, ensuring the content is current and applicable to current research. Even for experienced qualitative researchers, Silverman manages to create a valuable summary of everything you need to consider to conduct a rigorous analysis.

I would recommend this book to anyone who is conducting a qualitative study, whether they are a student researcher new to qualitative analysis, or a more experienced researcher wanting to refresh their knowledge on interpreting data. In my opinion, Silverman surpasses others in his content and style, making this book one of the leading reference tools available on qualitative research.

Demystifying evaluation: practical approaches for researchers and users
David Parsons
Policy Press, 2017

Reviewed by Jane Evans, Fine Grain Consultancy

I learned a great deal from this concise but hugely practical book. The structure is accessible and clear, with chapters on conducting process, economic, and impact evaluations, based on the fundamental elements of compilation: setting the right foundations; and composition: designing for needs. I also appreciated the glossary and clearly set out annexes. Parsons aims to provide a short, practical guide for a range of readers, covering an array of evaluation methods and highlighting some pitfalls. He more than achieves this, and so he should, because an important part of the message of this work is the essential task of setting SMART objectives in compiling an evaluation.

As a qualitative/mixed methods researcher myself, I found the chapters on economic evaluation and experimental methods particularly informative. While I may not use most of those models, I am pleased I now understand more fully how they fit into the field.

Although this book is mainly intended to be used by evaluators, I would recommend all those procuring an evaluation to read chapters two and three on compilation and composition before setting out their tender or commissioning documents. Many organisations are looking for an evaluation to please the funder, but are unclear about what they should, or could, ask of an evaluator. Similarly, reading this book has given me the confidence to offer a stronger steer to commissioners, especially when they seem unsure of what can and cannot be achieved through an evaluation. Parsons’ guidance that ‘ideally, decisions on scale should lead decisions on budget, and not vice versa’ is one I would commend to everyone involved in designing an evaluation.

Communicating your research withsocial media: a practical guide to usingblogs, podcasts, data visualisations and video
Amy Mollet, Cheryl Brumley, Chris Gilson and Sierra Williams
SAGE, 2017

Reviewed by Andrew Richardson, independent researcher

This is an engaging and highly readable book. The authors deftly weave the theoretical with the practical, and include relevant and inspiring examples of how ‘knowledge workers’ can make use of social media across the full research life cycle. The authors define ‘knowledge workers’ as ‘academics, researchers, students, and communication professionals looking to understand more about research’. As a doctoral candidate nearing completion of my thesis and with ‘dissemination’ in mind, I found the chapters focused on blogging, infographics, data visualisations and podcasts both instructive and inspiring. Strategies to reach wider audiences and to achieve greater impact with research will appeal to researchers and other knowledge workers across a wide range of disciplines. Importantly, the authors also explore issues of copyright and navigating the risks of online visibility and, in so doing, speak to some of the anxieties that may be barriers for some researchers making greater professional use of social media. A companion website adds another level of engagement for the reader with good use of videos and blogs to bring the topics to life and illustrate what is possible with social media.

The authors set out to demonstrate that social media matters, and can be incredibly important to the work and careers of knowledge workers. In my view, they succeed in this ambition. In such a fast-moving digital world, I thought the authors’ hope that the book offers ‘as timeless a guide as possible’ was a noble but somewhat tall order. Revised and updated future editions are, however, warranted and well deserved.

An Adventure in Statistics: the reality enigma
Andy Field
SAGE, 2016

Reviewed by Marguerite Adewoye, Research Impact Unit, Department for Education

This book gives readers a solid grounding in basic statistics and in introductory R, a programming language and open source statistical computing package. It’s an excellent resource and successfully makes statistics more accessible. I would recommend it for people who are new to statistics, for example in social sciences degrees, or those who have used statistics without formal training, but need to pick up a full grounding in statistical theory without the benefit of a lecturer to guide them.

In this book, the statistical theory is cleverly embedded in a sci-fi novel. The story gives the reader a very good reason to start right back at the basics. One of the benefits of this approach, is that readers don’t accidentally skip a basic principle or statistical notation which will be applied again in more complex theories. The book also uses earlier aspects of the story to act as reminders for previous lessons. Basic
statistics books are usually fairly weighty, and this book is no exception. However, the story format encourages readers to persevere and to complete the course. It also gives readers quirky (and therefore memorable) analogies with which to visualise or conceptualise the statistical theories.

Despite starting with the basics, covering statistics that most readers will have learned in secondary school, the tone is not patronising. It moves steadily to more advanced topics of variance and dispersion, probabilities, central limit theorem and hypothesis testing. The most advanced topics covered are probably general linear modelling, including methods for different kinds of experimental or research designs, and factorial designs. The inclusion of simple instructions for the open source R statistical package is also a boon for newcomers to statistical analysis.