Example of using sporadic conversations as a research method

Great example of how to engage with the target group of your study by sporadic conversations. The original source is an article on Trump victory and the reality of rural areas in US. In it, the political science professor at the University of Wisconsin-Madison  Kathy Cramer speakes about his last book The Politics of Resentment, where she traces the rise of conservative Governor Scott Walker and the political evolution of Wisconsin. What Cramer says she found is that a strong sense of rural identity in the communities she visited has become a key driver of political motivation in Wisconsin. And over time, that sense of rural identity has come to be largely defined as an us vs. them mentality, with the them being people who live in cities.

Here I paste the most relevant parts regarding the methodology applied:

…what I did was to sample a broad array of communities in Wisconsin. And I asked people who lived there, “Where in this community do people go to hang out with one another?”

What’s important to understand is that these were not one-on-one interviews, these were not focus groups of people I assembled. These were groups of people who, for the most part, meet with each other every day, and they’ve been doing so for years. So I was inviting myself into their existing relationships in the places they already meet. I think that’s part of the reason why I was able to get the local texture. It wasn’t like trying to invite them on to the university campus and then trying to glean what I could out of them. Obviously the conversation changed a bit because I was there and asking questions. But these were groups of folks who were really used to talking with one another about politics.

This group was all men, older, some on their way to work and some retirees—so kind of the Trump demographic. I said to them, “What do you hope that Trump changes? Like, five years from now, what differences do you expect to see?” And initially their response was well, nothing. Nothing that presidents do ever affects us here in this place.


Gentrification of a postsocialist old centre in Gdansk, Poland

Yesterday, walking from industrial area in the surrounding of Gdansk until the historic old center. It was worth photographing the difference in terms of housing in hardly half a kilometer, as well as the contrast between old industrial sites by the river and the new real state that is being raised. The river side is experiencing a growing gentrification process. The ruins of second war, a kind of open air museum of how WWII destroyed the city are becoming debris while the city invest in a huge and modern museum of WWII. Komfort investment firm is building a luxury and privilege view condominium near the river.


Postsocialism and postindustrialism: how outsourcing and offshoring boom is transforming Gdansk city, Poland

Gdansk city is emerging as the next outsourcing city. As many other mid-size cities in the country in the last decade, as well as the capital Warsaw did since 1990, the city is harbouring a increasing number of multinational corporations that aim to outsoource certain business process. In a preious post I echo a very interesting article on the boom experience in this city due to the arrival of BPO to the city (Business Process Outsourcing). They represent nowadays the 30% of employment. As suggested by the major in that article, the “boom” is “rebranding the city”. This photos, taken at the so called “Oliwa Gate, the district where most of the BPO are being located, try to reflect visually this phenomenon.

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“It’s about the depth of your data”

Fantastic article (it’s about the depth of your data) on “qualitative data analysis”, clarifying the difference between “quali” and “quanti”, but also providing rich comments on the labour of fieldnotes when doing fieldwork. I want to emphasize this parragraph and then you can read the whole article:

Descriptions in fieldnotes need to be precise. Rather than using the word “said” for example (as in “She said”) we encourage sociologists to think more deeply about the way in which the communication unfolded. Did she seem angry, bored, thoughtful, unsure, frustrated, annoyed, or sad as she spoke? Was his tone of voice loud, boisterous, gentle, irritated, exasperated, discouraged, delighted, gleeful, cheery, or jovial?

Another great sentence:

Data analysis is ongoing and deeply entwined with data collection.

Here is the whole article:

A key strength of in-depth interviews and ethnography is obtaining textured insights into social phenomenon. Yet, many qualitative researchers try to invoke the reliability of quantitative methods by shrouding themselves in numbers as a way to legitimize their work. They offer up the number of interviews, the number of hours, weeks, and years spent in the field and they propose bigger and bigger samples. Even as qualitative researchers assert that they have carried out in-depth qualitative research, they often revert to the language of quantitative research to justify the legitimacy of the work. The nod to numbers is a way of claiming trustworthiness and, importantly, scientific expertise, which is usually equated with quantitative methods. This dependence on large sample sizes for qualitative research as a form of legitimacy, however, is misplaced. Indeed, we see this seeking of legitimacy through quantification as a distortion of where the value of qualitative research truly lies.

Instead, it is the depth of qualitative data that determines the quality of the work. Qualitative methods have the capacity to illuminate meaning—particularly the micro-level nuances of attitudes and daily behaviors. Qualitative research can highlight the impact of large-scale social structural forces on the rituals of daily life as well as many other spheres of life. This depth may in fact be linked to a larger number of interviews, or to more time spent in the field, but it should not be seen as reducible to this. We want to point to three factors that we see as being indispensable to achieving depth in qualitative research: collecting high-quality data, trenchant data analysis, and vibrant writing.

Qualitative data has the advantage of making readers feel they are hearing the interview or seeing the scene unfold in their presence. Our trust of qualitative data should thus rely (more than it currently does) on how vividly the researcher captures the micro-level nuances. The point is to study social interaction—how people act and how others react to their actions, as well as how people react to the reactions. Descriptions in fieldnotes need to be precise. Rather than using the word “said” for example (as in “She said”) we encourage sociologists to think more deeply about the way in which the communication unfolded. Did she seem angry, bored, thoughtful, unsure, frustrated, annoyed, or sad as she spoke? Was his tone of voice loud, boisterous, gentle, irritated, exasperated, discouraged, delighted, gleeful, cheery, or jovial? (A thesaurus is a crucial aid here.) The notes should be greatly detailed. Lareau’s rule of thumb for the data collection for Unequal Childhoods was to spend five to twelve hours writing fieldnotes after every two or three hour visit. At the very least, researchers want to take twice as long to write up their notes as they spent in the field.

These kinds of notes also can set the stage for description of interviewees. Although notes usually cannot be collected during the interview—since it breaks the flow and the connection between the respondent and the interviewer—they can be written immediately afterwards and must be done within 24 hours. As part of the creation of a high-quality data set, it is crucial to collect information on facial expressions, gestures, and tone of voice so as to better understand the social interactions being studied. It is also helpful to highlight the sounds, smell, and light in the setting researchers are trying to describe. Qualitative researchers want the reader to feel as if he or she is peering over the researcher’s shoulder to watch the events which are unfolding. But this kind of depth traditionally comes at the cost of scope in the number of sites and also in the number of interviewees. (Many researchers have concluded that they can keep about 50 people in their heads during data analysis.) Extremely large studies are difficult for one researcher to carry out, are expensive to transcribe, and are hard to represent through words. Smaller studies may create difficult decisions on balancing groups to study, but all studies involve hard choices. The goal is to achieve deep knowledge in a particular research setting.

Data analysis is integral to data collection in qualitative research. As the first bits of data emerge, researchers should read over fieldnotes and interview transcripts to search for emerging themes. Throughout the data collection process, researchers should consider the research question and try to figure out what interesting themes are surfacing. This analysis is almost always a pattern of discerning a focus (and letting go of other, interesting questions). But it is important to be skeptical as well. Researchers should search vigorously for disconfirming evidence to the emerging ideas. In the data analysis for Unequal Childhoods, for example, Lareau searched assiduously for middle-class, working-class, and poor families who had different behaviors than the general pattern for their social class. She found one white mother, who was raised in an affluent home, but—as a former drug addict living below the poverty level—her parenting style followed the “accomplishment of natural growth,” which was the cultural logic of child rearing in working-class and poor families. These and other examples increased Lareau’s confidence in her findings. In other cases, if researchers find disconfirming evidence, they need to investigate it thoroughly. Is it the exception that proves the rule? Or does it mean researchers should rethink their conclusions? Sociologists want to capture patterns that are decisively in the setting they are studying, and they want to be alert to variations on a theme. Writing memos, talking with others, giving “works-in-progress” talks all are helpful strategies to try to figure out what researchers are really doing in the field. Data analysis is ongoing and deeply entwined with data collection.

Our last point is that high-quality research is well written. Because doing qualitative research well is labor and time-intensive, it can be frustrating for scholars that they cannot share all of the collected evidence with the reader. Instead, researchers only share an extremely small fraction of the data. But qualitative researchers know that they have more data to support their claims than what they are able to present. This conviction is important. Yet, the writing and the quotes need to be judicious. Readers enjoy being told a story, and readers like to “connect” with a person in the text. Researchers who collect and analyze these rich details of social interaction are able to create clearer, more sophisticated arguments. Hence, it is valuable for these details to appear in the analysis. Too many studies using interview data prioritize including numerous quotes on the same analytical point as evidence of the robustness of their data. We find it better to present fewer people in more depth by helping the reader get to know a person in the study. For example, rather than presenting disembodied quotes in a research report, we believe it is ideal to help the reader understand who is speaking. Even in a brief fashion, the author can bring the respondent to life. This can be done by delving into the relevant back-story of the participant, detailing facial expressions, gestures, and tone of voice. Then, the common themes can be illustrated more briefly with evidence from others. Tables also can be a succinct way of capturing patterns in the sample with very brief quotes—often less than ten words—which illuminate key themes.

In the end, qualitative research is about words. It is not about numbers. The “arms race” to have bigger and bigger samples is unfortunate, since many researchers spend valuable time and energy collecting data only to leave it on the “cutting room floor.” Qualitative researchers need to evoke in readers the feeling of being there. But that knowledge of daily life comes from learning the details of a relatively small, non-random sample. It means systematically analyzing the experiences, looking for disconfirming evidence, and being sure that the patterns are solid. It also means bringing them to life through the written word. The value of qualitative research is not about brandishing the large number of cases in a study. Instead, qualitative researchers need to focus on the quality and the meaning of the data they have collected. This is the source of their legitimacy.

Annette Lareau is in the sociology department at the University of Pennsylvania. The author of Unequal Childhoods, she is writing a practical guide for doing ethnographic research.

Aliya Hamid Rao is a doctoral candidate in the sociology program at the University of Pennsylvania. She is completing a dissertation on how gender reverberates through the unemployment experiences of families of white-collar men and women.

Advantages of interview in pairs

I came accross this article on “want to improve your qualitative research? try using representative sampling and working in teams” and I found interesting the advantages authors highlight with regard to do interviews in pairs:

Teamwork was woven into all aspects of the project. For example, we often interviewed in pairs. This was partly for safety, but also because it was easier for one person to drive while the other navigated, to call a youth to let him know we were on our way, or to begin writing the field notes on the return trip home. But the primary reason is that it improved the quality of the data. We have all watched each other conduct interviews and given feedback on how the other person could have done it better, or what was missed. We debriefed as a team on a weekly (sometimes daily) basis, talking about the day’s interviews, what we noticed, what surprised us, and what patterns we were observing. Was there something in the interview guide that needed updating because of recent events? Did the team understand the terminology someone used when describing her sexual or romantic relationships?

An additional advantage to team research is that it’s much harder to make a mistake when others who read and comment on your work have all been in the same neighborhoods, interviewed others from the same family, and have read the same transcripts. Often, during the course of analyzing and writing, we were challenged by colleagues who questioned whether a given conclusion is warranted. That kind of feedback sent us back to the drawing board more than a few times.

“how to do ethnography right” by syed ali and philip cohen in Context

See bellow a great article by syed ali and philip cohen (March 19, 2016) in Context. I also want to bring here one of the comment you can see in the original source: “Ethnography is much needed where genarised beliefs, stereotypes and invalidated generalisations direct policy”

Ethnographies are works of deep research based on in-depth, open-ended interviews and keen observations of how people go about their lives in different contexts. Researchers often spend years in their research sites to get to know the people and places they study in a way that can’t be done using other methods. Ethnographies are (arguably) the most visible and relatable research products that sociologists have to offer the general public. They tell stories about our social world backed up by rigorously gathered data. That’s pretty cool.

While ethnographers are very much expert in their research domains, their work is increasingly subject to public scrutiny. It is important for sociologists to develop and maintain professional standards that allow them to conduct the best research without compromising quality in the face of potential criticism and controversy. Recent conversations about the practice of ethnography have been spurred by the responses — public and academic — to high profile books in the past few years. But that is just the current manifestation of an evolving dialogue about the best way to do ethnographic work. A number of important issues have featured in this conversation: data preservation and sharing, replicability and confidentiality, peer review, funding and research support, and others.

At the suggestion of the American Sociological Association’s Council, we organized this special forum with some of the top practitioners in the field. Here you’ll find six papers that lay out “best practices” for ethnographers to follow. (Follow the links to read more!)

  • We start with Dana R. Fisher’s paper, “Doing qualitative research as if counsel is hiding in the closet.” Whether you study elites or study the poor, Fisher says you should do your research as if the group you’re working with has legal representation. It could save you headaches (and money, and even your reputation) down the road.
  • Ethnographers for the most part work alone, and they use convenience sampling, that is, they talk to people who are conveniently located for them to talk with. Stefanie DeLuca, Susan Clampet-Lundquist, and Kathryn Edin argue in their essay, “Want to improve your qualitative research? Try using representative sampling and working in teams,” that ethnographers can, and should, well, use representative sampling and work in teams. This will improve the depth and reliability of your data and your story.
  • Another common practice that ethnographers do by default is to provide anonymity for the people they interact with and the places where they do their research. In “Ethnographic masking in an era of data transparency,” Alexandra Murphy and Colin Jerolmack debate the merits of this practice and, for the most part, find it to be unnecessary and, for the purposes of scholarship, counterproductive. They argue that our default practice should be to name names and places, unless there are specific case-by-case reasons not to.
  • Sometimes researchers are stymied when they’re trying to study populations that are difficult to get a hold of. Kimberly Kay Hoang and Rhacel Salazar Parreñas tell us how they were able to reach out to, and conduct research with, a broad range of sex workers in Vietnam, and domestic workers in Dubai, in their essay, “Accessing the hardest to reach population.”
  • It has become standard for social science researchers to gain approval from their university’s Institutional Review Board before they start work on a project. This can be frightening and frustrating. Abigail E. Cameron gives practical advice in her paper, “The unhappy marriage of IRBs and ethnography,” for how you can navigate the IRB process painlessly. (Ok, less painfully.) Even controversial topics can gain approval if you approach your IRB in the right way.
  • The last paper here is by Annette Lareau and Aliya Hamid Rao, “It’s about the depth of your data.” They remind us that ethnographers are not quantitative researchers, and that the small, nonrandom sample ethnographers usually have actually isn’t a problem — in fact that’s a selling point for ethnography. The ethnographer is telling the reader a story, and Lareau and Rao tell us that detailed fieldnotes, lengthy interviews with smaller numbers of people, smartly developed themes and analyses, and crisp writing are the key to good ethnographic storytelling. Sometimes ethnographers forget these things. It’s good that Lareau and Rao are reminding us.

Taken together, we shouldn’t consider these as a blueprint for criticism-free research or a set of “how to” papers. But it’s close. So read, learn, enjoy—and if you’re an ethnographer, go forth and do your thing!

why blog your field work?

Great post! Another good reason to do so is that not only participants but also co-researchers and/or supervisor, know more about what you’re doing.


Over the last week I’ve posted every day about the ethnographic research I was doing at the Tate Summer School, research carried out with the Tate Schools and Teachers team. Why? Why did I interrupt my normal flow of writing about academic writing and research with a set of posts about my own research? Why was I blogging my research at all?

A lot of people tell me that they are worried about posting about research that is so clearly work in progress. But I want to convince you that there are some good reasons to do so, particularly if you’re doing qualitative work with real live people. And here’s a few of them:

(1) it’s a good record. Writing a blog post forces me to focus on providing a straightforward account of what went on each day. I have to choose the key points and write them succinctly. The…

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