Our four peer researchers gave a wonderful presentation of findings so far for the supported decision making research project at the Knowledge Exchange Seminar (KESS), Parliament Buildings, Stormont, Belfast on the 7th February 2018.
Our research team will be giving a presentation on Supported decision making – experiences, approaches and preferences at the Knowledge Exchange Seminar, Long Gallery, Parliament Buildings, Stormont on the 7th February 2018.
So why not take a look at the abstract and register to attend if you are around?
Making decisions about your own life is a key aspect of independence, freedom and human rights. Mental health law has previously allowed compulsory intervention even when a person has the decision making ability to decline intervention. This discriminates against those with mental health problems and intellectual disabilities. In May 2016 the Mental Capacity Act (Northern Ireland) became statutory law, although may not be implemented until 2020. In contrast to other countries this law will replace rather than be in parallel to a mental health law. This is a unique and progressive development which seeks to address the discrimination of separate mental health law. A core principle of the new Act is that people are “not to be treated as unable to make a decision…unless all practicable help and support to enable the person to make a decision about the matter have been given without success” (Article 1(4)).
There are people who, without support, would be assessed as incapable of making certain decisions but with the appropriate support are capable of making those decisions, and so to not provide that support infringes their rights, undermines their autonomy and reinforces their exclusion from society. There is very limited research evidence available about people’s experience of the range of approaches provided to support decision-making; what approaches work for whom; and what people’s preferences are for support. This evidence is urgently needed to inform the Code of Practice for the new Act and the wider implementation process.
This presentation provides a summary of findings from a research project which explored how people have, or have not been, supported to make their own decisions. It was funded by Disability Research on Independent Living and Learning (DRILL) and used a coproduction approach between disabled people, Praxis, Mencap and Queen’s. The project involved peer researchers interviewing 20 people with mental health problems and 20 people with intellectual disabilities, to gain an in-depth understanding of their experiences of supported decision-making and their preferences and ideas for how decision-making should be supported in the new legal framework.
Hammersley, M. (2014) The limits of social science. Causal explanation and value relevance
In this short book, Hammersley argues for a social science which eschews grand theorising in favour of the explanation of social phenomena. Drawing inspiration from Max Weber and referring to a range of social theorists and philosophers, Hammersley encourages social scientists to re-think what they are actually doing as researchers in order to create a social science which generates knowledge which is both reliable and valid. Some readers might, of course, reply that there are no problems with social research as an intellectual endeavour, but Hammersley’s purpose seems to be to awake us from our slumbers. This is a task in which he partially succeeds. Hammersley is not, for example, opposed to causal analysis in the social sciences, but argues that we should raise our game by adopting ‘within-case and cross-case analysis’. He also prioritises explanation over theorising with the proviso that ‘all purpose’ explanations are not possible because explanations are ‘always answers to particular questions’. He also argues that value conclusions cannot be derived from evidence, and offers convincing arguments why this might be the case. The consequence of Hammersley’s position is that social research should be limited to making ‘factual’ statements rather than ‘value’ claims. Although much of the book is theoretical, the author grounds his views by referring to social mobility research and to work on the English riots of 2011.
What I most enjoyed about this book is that Hammersley encourages the reader to think hard about social research practice. He is, for example, unconvinced by the view that there is a direct relationship between research and policy outcomes. On the contrary, he says that the relationship is ‘highly mediated and contingent’. Moreover, he recognises that different social science disciplines employ different methods of explanation. One has only to think of the very different approaches of the experimental psychologist and of the historian to appreciate that he has a point. But such explanatory pluralism in the social sciences has a disturbing consequence. If there is no agreed threshold which all social scientists have to meet in order to generate valid and reliable knowledge, then how do these disciplines differ from vocations like investigative or data journalism? In addition, Hammersley draws a sharp distinction between ‘facts’ which are of interest to the social scientist and ‘value claims’ which should be of interest to policymakers and think tanks. If true, it is very hard to see how social researchers can make the case for funding their work in a cultural environment which does not recognise that knowledge has value in itself. Hammersley recognises this point but does not offer any solutions.
This book is not a paean to social science as it is currently practised and will be, to use Hammersley’s own word, a ‘deflationary’ read for some. If, however, you want to read something which may question your preconceptions, this book is a good place to begin.
Review originally published in Research Matters, December 2015
Charmaz, K. (2014) Constructing Grounded Theory
If you need a clear introduction to grounded theory, then you will find it here. Charmaz describes grounded theory’s genesis, and explains how to code, write and sort memos and engage in theoretical sampling. This second edition includes new material on interviewing and symbolic interactionism.
She supports what she is saying by referring to her own research and that of others working in diverse fields. She manages to convey the excitement of conducting a grounded theory study which will, I’m sure, make readers think how they can apply her techniques. Information is easy to locate as main points are presented throughout the text. This means that the reader can either read the text linearly or source what they want later.
It succeeds as a book about methods but it is much more than this. Charmaz skilfully situates grounded theory within its historical context by showing how Glaser and Strauss – the pioneers of this approach – were influenced by the ‘Columbia University positivism’ of Paul Lazarsfeld and Robert Merton and the ‘Chicago school pragmatism and field research’ of sociologists such as Herbert Blumer. She devotes an entire chapter to symbolic interactionism – a ‘theoretical perspective that views human actions as constructing self, situation and society’. She also shows how her own ‘constructivist’ approach to grounded theory contrasts with that of ‘objectivist’ theorists who adopt the position of a neutral observer and consider that they are studying worlds which are entirely external to themselves. For Charmaz, meaning does not exclusively inhere in the data, which is a position which may be troubling to those who assume a clear separation between ‘facts’ and ‘values’.
Although convinced that symbolic interactionism and grounded theory are a ‘theory-method package’, she readily concedes that grounded theory may be used with other theoretical perspectives. As she would say, theoretical ‘purity fosters preconception’. Although one might think that her meditations on ontology and epistemology may be heavy going, her writing is simple and informal, and she always shows how her theoretical views connect to the practical business of doing research. These sections require careful study but are the most rewarding.
This is an excellent book. It is easy to read, gives lots of practical advice and is quite profound. If you are serious about studying the conceptual universes and the interior worlds of research participants in a way which recognises that the researcher is intimately involved in the construction and analysis of data, this is a book which will make you re-think how you conduct research.
Review originally published in Research Matters, September 2015
Nippert-Eng. (2015) Watching Closely: A Guide to Ethnographic Observation
Books on research methodology can be written in a dry, unengaging and inaccessible style which severely curtails their readership. After even a cursory reading of Watching Closely: A Guide to Ethnographic Observation, it becomes very clear that this book differs markedly from the more usual methodological fare. Not only is the book written – I think successfully – for a very diverse audience that includes students and practitioners across the social and behavioural sciences, but it also focuses on the ‘craft’ of being a fieldworker.
Christena Nippert-Eng – a sociologist and Professor of Informatics at Indiana University – not only shows how to conduct ethnographic observation, but also exhorts the reader to get out into the world to do fieldwork for themselves. The book is therefore both a pedagogical text which explains how fieldwork should be done, and a fieldwork companion, which the researcher can carry with them and reuse irrespective of their level of experience. The author does of course recognise that one can collect data using conversation and participation, but her focus is on observational data because of the dearth of skills in this area. This is an assessment with which I am inclined to agree.
Watching Closely is divided into three parts: ‘Getting Ready’, ‘The Exercises’ and ‘Moving Forward’. Part One tells the reader how to use the book and about the author’s philosophy of fieldwork, which she herself characterises as one of moderate social constructivism (19). Modelling the book on a ‘fine arts or studio course’ (5), the emphasis is on exercises in the second part, which focuses on particular concepts and allows the reader to practise their data collection, analytic and report-writing skills. Part Three then brings the book to a close by offering advice on what one should do in order to develop as a fieldworker.
As the second part forms the core of the book, I’ll give the reader some idea of what is involved. Nippert-Eng advocates ‘concept driven’ fieldwork (36), with a particular focus on ‘time’ and ‘space’ and, where possible, on non-human animals. Her preference for the non-human subject is reasonable as she is trying to inspire readers to observe attentively rather than to ascribe motivations to behaviours, which would perhaps be the case when studying human subjects. The nine exercises therefore encourage the reader to use the author’s toolkit of concepts to make sense of data in the field.
Prior to doing each exercise, Nippert-Eng invites us to think sociologically. In the second exercise on ‘temporal mapping’, for example, she provides a short but fascinating discussion of the distinction between ‘natural’ and ‘artificial’ time, with reference to the work of the sociologist Eviatar Zerubavel, as a prelude to asking the student to construct a ‘temporal map’ of their own. This involves selecting a body part of the animal being observed and ‘describing its movements’ with reference to time (87). The reader is then encouraged to write up a report of the exercise before reading the ‘Post-Exercise Discussion’ and the ‘Mechanics of this Exercise’ sections. The student then follows a similar process in the third exercise – again on ‘temporal mapping’ – with the objective being to extend their understanding of the concept of temporality by taking account of duration, sequence, pulse, repetition and cyclicality (120).
Although this discussion of the exercises may seem abstract, nothing could be further from the truth as Nippert-Eng grounds her advice with concrete references to her own field of study: namely, the gorillas of Lincoln Park Zoo, Chicago. Readers are also encouraged to refer to sample responses to each of the exercises on a dedicated companion website. Indeed, I was captivated by this feature of the book due to the imaginative, creative and insightful ways in which each student presents their findings. The author really manages to convey the excitement of conducting research in the field. Not only will anyone who reads this book and completes the exercises improve their ability to collect observational data, but they will also come away from the text itching to do their own research.
Moreover, the decision to limit discussion to a small subset of problems is wise if one considers that inexperienced researchers can often feel overwhelmed by the amount of data which is available. The problems are also well chosen because they provide the researcher who does not have a clear focus with conceptual hooks which they can use to think about the problems that interest them before going out into the field. Each exercise also carefully builds on what has gone before. Nippert-Eng is therefore sensitive to the challenges posed by ethnographic research.
The author also manages to combine a lot of very tangible advice with a style that poses questions which the reader is invited to solve for themselves. I thought, for example, that her discussion of the challenges posed by the attempt to collect observational time series data was particularly thought-provoking. In addition, the eclecticism of the scholarly sources on which she draws is truly impressive. The reference to the work of Scott McCloud on Understanding Comics may seem tangential, but it is exceptionally relevant when one remembers that Nippert-Eng is making a point about the importance of storytelling for researchers who wish to re-present their data effectively. The sheer breadth of the sources on which she draws is therefore a reminder of how researchers should work in an interdisciplinary way if they wish to truly leverage their data and understand the social world.
In short, this book is an exemplar of how books on research methodology can, and perhaps should, be written as Nippert-Eng combines solid instruction in the technicalities of ethnographic research with a set of useful exercises which will convince the reader that research is fun, insightful and a craft skill that one can acquire through practice.
Review originally published in LSE Review of Books and LSE USA Politics and Policy March and April 2016.
It is possible to identify top level categories in qualitative data analysis by using text mining methods. One can count the frequency of terms or words in a text or texts. Words which occur frequently may be top level classifications or themes.
Text mining involves the creation of a corpus or collection of texts for analysis, some initial work to preprocess the corpus so that punctuation, capitalisation and numbers are removed as well as common words which are, ipso facto, very frequent in any text. A document term matrix is then created where the documents in the corpus are represented by rows and the words by columns. Analysis could then include identification of frequent terms and a ‘frequency of frequencies’ i.e. how many words occur in a corpus at specific frequencies?
For further detail, check out Kailash Awati’s Gentle Introduction to Text Mining with R here and an RStudio resource here which describe how to text mine with R’s tm package. The RStudio link also includes additional links to books on text and data mining as well as material on ‘clustering’ methods.
Both tutorials assume that R is already installed. If this is not the case, go to The R Project for Statistical Computing here and follow the instructions for your system.
R binaries are available for Windows, Mac and Linux distributions.
The R package RQDA may be one alternative for qualitative researchers who do not have access to, or do not wish to use, proprietary CAQDAS software. RQDA allows the user to import text files, create codes and file categories and to visualise file categories with sociograms.
It’s also possible to run the package from the command line and to export RQDA data to LaTeX.
Further information is available from: