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Good, the Bad, and the Data: Shane the Lone Ethnographer's Basic Guide to Qualitative Data Analysis

Galman, Sally Campbell

Left Coast Press, (2013)
ISBN: 9781598746327 (pb)

Reviewed by Kevin Walby, University of Victoria

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Cover of Good, the Bad, and the Data: Shane the Lone Ethnographer's Basic Guide to Qualitative Data Analysis The Good, The Bad, and the Data by Sally Campbell Galman is an alternative comic book about the basics of qualitative research methods. Galman herself is trained in anthropology and education. She provides the snappy captions as well as the drawings for this alluring text. The Good, The Bad, and the Data follows Shane, a graduate student whose adventures lead to encounters with discourse analysis, narrative analysis, and more. The text is laced with allusions to 20th century Western films as a quirky way of depicting the adventurous quality of qualitative research.

First we meet up with Shane when she is in the middle of a conundrum: just how does one do data analysis? Galman walks Shane through the idea that research requires ‘cookbooks’ or instructions that spell out in detail what procedures to follow. These instructions should also: give tips about traps; be precise but not too rigid; be open to change; and be complex. Shane learns that anyone writing up a methods section should aim to provide a set of instructions like this for readers. It is also imperative to create a data matrix for any project, which sets out what material you have to work with and what you do not. The next chapter deals with debates about art and science. Galman compellingly contends that qualitative data analysis requires both art and science to categorize and interpret data. The early chapters of The Good, The Bad, and the Data are absorbing and engaging. Shane learns about data fracturing as well as induction and deduction, all of which are illustrated using cartoons. Shane also contemplates the practice of coding, again through illustrative examples that help explain the difference between inductive and deductive approaches. Galman offers an enlightening exploration of one type of grounded theory as well.

In each chapter there are small vignettes on analysis techniques, which can be cut out and pasted into a research diary. Lining them up in order provides a cookbook for understanding the basics of qualitative research methods. At the end of each chapter, there is also homework that Galman assigns, which encourages the reader to get busy with the ideas presented. There are lots of active components in The Good, The Bad, and the Data, which should broaden the appeal for students.

What comes next are chapters on narrative analysis, discourse analysis, as well as analysis of videos and pictures. Shane learns about the basics of each approach. My only concern is that these chapters are much shorter than and not as detailed as the earlier chapters. The earlier chapters are totally effective and compelling. Equally descriptive chapters on narrative analysis, on discourse analysis, and on analysis of videos and pictures would be a very welcome contribution, since it is in these specific approaches that researchers often get lost. The Good, The Bad, and the Data is called a ‘basic’ guide so I hope that the next book provides more on these approaches and others (e.g. metaphor analysis, institutional ethnography).

The chapter on writing suggests that exposition is as much or more work than analysis, and is an important part of analysis itself. Galman provides guidance on exposition, which supplies a good set of tips for beginners and reminders for established scholars. The Good, The Bad, and the Data concludes with advice for how to make it through the tough times and doubts that all researchers face, as well as with commentary on triangulation, auditing, reliability, and validity. This is one part that I have trouble with. Not all qualitative researchers strive for reliability, validity, or generalizability as end goals. Some prominent scholars have made arguments against using those as criteria for guiding qualitative work or interpreting the work of others. Tracey’s (2010) argument that reliability, validity, or generalizability are not consistent with qualitative research is important to keep in mind. However, when teaching newcomers to qualitative research, I concede that keeping it simple and making reference to these standard social science tropes is probably the safest way to go.

The Good, The Bad, and the Data provides a wonderful introduction to qualitative research practice. First and second year undergraduate students as well as highschool students in any social science discipline should read this text. It will teach students how to think and work like a qualitative researcher. It illustrates how to code data in ways that other texts do not. And it has the right robust spirit. Qualitative research is always an adventure.


TRACEY, S.J. 2010. ‘Qualitative Quality: Eight “Big-Tent” Criteria for Excellent Qualitative Research’. Qualitative Inquiry 16/10: p.837-849.