Monthly Archives: March 2016

Health and happiness: cross-sectional household surveys in Finland, Poland and Spain



To explore the associations between health and how people evaluate and experience their lives.


We analysed data from nationally-representative household surveys originally conducted in 2011–2012 in Finland, Poland and Spain. These surveys provided information on 10 800 adults, for whom experienced well-being was measured using the Day Reconstruction Method and evaluative well-being was measured with the Cantril Self-Anchoring Striving Scale. Health status was assessed by questions in eight domains including mobility and self-care. We used multiple linear regression, structural equation models and multiple indicators/multiple causes models to explore factors associated with experienced and evaluative well-being.


The multiple indicator/multiple causes model conducted over the pooled sample showed that respondents with younger age (effect size, β = 0.19), with higher levels of education (β = −0.12), a history of depression (β = −0.17), poor health status (β = 0.29) or poor cognitive functioning (β = 0.09) reported worse experienced well-being. Additional factors associated with worse evaluative well-being were male sex (β = −0.03), not living with a partner (β = 0.07), and lower occupational (β = −0.07) or income levels (β = 0.08). Health status was the factor most strongly correlated with both experienced and evaluative well-being, even after controlling for a history of depression, age, income and other sociodemographic variables.


Health status is an important correlate of well-being. Therefore, strategies to improve population health would also improve people’s well-being.

Miret, M., Caballero, F. F., Chatterji, S., Olaya, B., Tobiasz-Adamczyk, B., Koskinen, S., … & Ayuso-Mateos, J. L. (2014). Health and happiness: cross-sectional household surveys in Finland, Poland and Spain. Bulletin of the World Health Organization, 92(10), 716-725.

Four urban conditions of vibrant city life and reflection on megaprojects

Assuming the bellow showed Jacobs´ urban conditions of vibrant city life and that urban megraprojects tend to make urban spaces more homogenous due to the concentration of a particular service or user profile, do megaprojects kill vibrant city life in a long term?

Jacobs argues that vibrant activity can only flourish in cities when the physical environment is diverse. This diversity, she says, requires four conditions. The first is that city districts must serve more than two functions so that they attract people with different purposes at different times of the day and night. Second, city blocks must be small with dense intersections that give pedestrians many opportunities to interact.

The third condition is that buildings must be diverse in terms of age and form to support a mix of low-rent and high-rent tenants. By contrast, an area with exclusively new buildings can only attract businesses and tenants wealthy enough to support the cost of new building. Finally, a district must have a sufficient density of people and buildings.

Jacobs, J. (1961). The death and life of great American cities. Vintage.



“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.

Ethical research tradeoff: masking or unmasking participants names and places

Outstanding article on ethics and particularly, on how to proceed when handling the confidentiality of respondents in a given research: “ethnographic masking in an era of data transparency” The common practice is to mask the names of participants and places as for the “do no harm” ethic. In this article, authors argue that the default practice should be to name names and places, unless there are specific case-by-case reasons not to. That way allow not omiting sometimes key informaiton. They sustain that in the Era of Internt, trying to mask names and places by using pseudonyms, at best, it seems “illusory promise to protect confidentiality”. What is more, participants often find seeing their names in print, when a book is published, “rewarding”.

We frame this essay as a conversation because, over the last few years, the two of us have been having a vigorous discussion about masking as we each grappled with methodological and theoretical challenges that masking was posing for our respective ethnographies in two different small towns. This conversation has evolved beyond our own work and resulted in an article that probes larger issues around the ethical and scientific tradeoffs of masking and challenges the usual justifications given for this practice. We want to use this forum to share some of our experiences and thinking on this matter and invite others to join us in the exchange.

Murphy (M): Our starting point is that masking has become virtually a ritualistic practice in ethnographic writing. When ethnographers sit down to write, they commonly assign fictitious names to the people and places they study. This is often justified as an ethical necessity, to protect our participants’ privacy and/or prevent them from being harmed from their participation in the research. But concealing identities is a slippery slope. Pseudonyms alone are seldom sufficient to protect confidentiality. And so ethnographers frequently engage in more extensive masking by, for example, altering identifying characteristics about people (e.g., changing a person’s gender or occupation) and places (e.g., altering historical events or census data), omitting primary source references, and/or creating composite characters. These practices run counter to the growing expectation for data accessibility and for making it possible for others to triangulate data sources and compare cases.

Jerolmack (J): It seems to me that one way masking does this is by burying sociologically significant information that can be used by the scholarly community to independently evaluate the ethnographer’s analysis and consider alternative interpretations. We discovered a great example of this in the book Forgive and Remember, an examination of the training of surgeons and the organization of their work in one hospital. In the book, Charles Bosk changed the gender of a female surgical resident in an effort to ensure her confidentiality. Almost 30 years after its publication, Bosk revealed that this participant was the only woman resident in the group. By altering her gender, Bosk made it impossible for a reader to consider how gender shaped hospital interactions and promotion practices. In hindsight, Bosk admits that gender was actually very central to understanding the social dynamics of the hospital, but it was something he did not notice at the time because of how his own gender was privileged in the field.

I don’t think ethnographers acknowledge the extent to which decisions about what and how to mask are inherently theoretical choices. Though ethnographers usually claim they are only making “minor” changes, to other scholars—especially those with different theoretical interests—they may be quite major and necessary pieces of information for them to come to their own conclusions about the role of particular biographical or situational factors in the analysis. As Bosk writes, “My problem with changing Jones’ gender is that it makes the critique I did not make impossible for others to make.”

M: Another problem with masking is that it makes generalizing beyond the ethnographic case difficult. Scholars often give places fake names, for example, to highlight how their case generalizes (e.g., “Middletown”) and to help move readers away from the case’s idiosyncrasies. But in my estimation, masking often removes the details a reader needs to specify what to generalize a case “to.” For example, in my work on suburban poverty, I have been documenting the ways that the built environment significantly shapes the social networks, neighborly relations, and survival strategies of people who don’t have cars or access to public transit. In analyzing my case, I turned to Carol Stack’s All Our Kin, a classic ethnography of survival strategies and kinship networks in an “African American ghetto” in the “Midwest” that she calls “The Flats.” Why, I wondered, do my findings about kinship networks differ from Stack’s? Unfortunately, I’m not able to explore whether differences in the built environment of the communities we studied account for some of these discrepancies because, in addition to concealing the location, Stack gives few details about the spatial configuration of the community or the networks she observed. She does note that her participants are spread out and that no one lives more than 3 miles apart, but what I have found is that living two blocks versus three miles apart or living in walking distance to businesses makes a significant difference in how these ties help people make ends meet. What kinds of communities can we generalize her findings to, then? To build a broader, more specified theory about poverty, race, place, and social networks, we need sufficient detail to answer questions central to making sociology a cumulative social science.

J: I’m also concerned with how masking can preclude replication, falsification, and comparison. The ethnographic revisit, for example, has been touted as an important way to study change over time. By revisiting someone else’s fieldsite years or decades later, ethnographers can use the original study as a kind of “baseline” comparison in order to specify how observed changes in interaction and the social order of the setting are the result of intervening historical forces. But when the scholarly community is denied the identity of places, organizations, and even people, making these types of revisits may be impossible for anyone but the original ethnographer, who remains the sole gatekeeper of the fieldsite and the knowledge produced about it.

Even if an ethnographer should serendipitously stumble upon a pseudonymous site that has been previously studied ethnographically, the original masking of the site constrains the later ethnographer’s ability to use the first study as a historical record. I am dealing with this dilemma in my current research project. When I moved to Williamsport, Pennsylvania in 2013 to study how shale gas extraction (“fracking”) is transforming community life, I was delighted to discover that an ethnography had been written about the area in the years just before fracking commenced. Since I had not been in the field before fracking began, having this earlier portrait of the community would enable me to specify how this industry has changed this town. The problem? In addition to using fake people- and place-names, the earlier ethnography masked numerous details about civic leaders, historical events, and organizations. That move now hampers my ability to directly compare changes over time among particular community groups.

Revealing place names can enable other kinds of revisits as well. For example, although my colleague Eric Klinenberg gave pseudonyms to the victims he wrote about in his bookHeatwave, his decision to name the city of Chicago and the two neighborhoods he compared allowed other scholars to quantitatively test his qualitatively-derived thesis about how differences in neighborhood-level factors contributed to disparate mortality rates across neighborhoods. Such comparisons enabled researchers to examine how representative Klinenberg’s neighborhoods were to other neighborhoods in the city andtest whether his claims about his own case studies were supported with other kinds of research techniques and data. All too often, however, such virtual or quantitative revisits are foreclosed by the ethnographer’s decision to mask place.

M: Many scholars may be inclined to concede that not masking identifying information would make ethnographic work more transparent—and, I think we both agree, more scientifically useful—but what would be the ethical implications of not masking, especially around issues of privacy and confidentiality? After all, it is our duty as researchers to “do no harm” to those we study. Colin, how do you think about this having already published a book where you do not mask and do not use pseudonyms?

J: My stance on naming was heavily influenced by a passage in Barbara Myerhoff’s moving portrait of an elderly Jewish community center (Number Our Days) in which she reveals that the seniors asked her to reconsider her decision to use fake names because they craved “an enduring record” of their existence. (She didn’t). The lesson for me was that I would give my participants a choice to be identified or masked, and in the end, only one person chose anonymity. There was very little that I could offer my participants for all the time they gave me, but they viewed seeing their name in print as intrinsically rewarding. When I handed out copies of The Global Pigeon, most quickly thumbed the pages looking for their name and some excitedly took photos of the printed pages they appeared on and texted them to friends and family. This has convinced me that, at least some of the time, naming may be more ethical than masking. It’s worth noting that I have gone through 3 different university IRBs, at both public and private schools, and have never had trouble getting IRB approval to reveal names for either of my ethnographies; IRBs do not in fact require pseudonyms or masking.

As for the “do no harm” ethic, it’s not clear to me that pseudonyms and masking actuallyprotect our participants. There are numerous instances where readers have identified the people, places, and organizations depicted despite the author’s efforts to scrub identifying information. Furthermore, masking also often fails in its goal to prevent participants withina fieldsite from identifying one another. A great example of this comes from what happened after the publication of Nancy Scheper-Hughes’ Saints, Scholars, and Schizophrenics. Not only did a reporter publicly unmask the Irish village that she called “Ballybran” but villagers also easily figured out the person behind each pseudonym despite the lengths she took to “scramble certain identifying information.”

M: It’s interesting to note that this example, and others like it, occurred long before the era of Google and social media. These technologies have made it even easier to identify people and places by performing keyword searches based on information or events depicted in an ethnography. I would guess that this is all the more possible given how much contemporary ethnographers have to interact with participants online to truly understand their social worlds, tethering us to our participants in very public ways.

J: Indeed. Given all of this, it seems to me that the practice of using pseudonyms and masking offers, at best, an illusory promise to protect confidentiality.

M: That’s exactly what Scheper-Hughes concluded as well. In fact, she wrote that if she were to write her book on “Ballybran” again:

I would…avoid the ‘cute’ and ‘conventional’ use of pseudonyms. Nor would I scramble certain identifying features of the individuals on the naïve assumption that these masks and disguises could not be easily de-coded…I have come to see that the time honored practice of bestowing anonymity on ‘our’ communities and informants fools few and protects no one—save, perhaps, the anthropologists’ own skin.

So Colin, are you saying that if we are not fully able to protect participants through masking we should do away with this practice altogether?

J: Not quite. Masking may be practically necessary to carry out some research and ethically required to carry out other research. But I think the universe of cases that “require” masking is much smaller than ethnographers acknowledge. Moreover, I believe that it is unethical for ethnographers to imply to our participants that we can promise confidentiality when it cannot—with any degree of certainty—be ensured, and that we should respect the fact that sometimes participants actually want to be named.

M: That makes sense, but I would add that participants should also have a right to decide if they don’t want their involvement in research to appear online when a friend, family member, lover, or employer Googles their name years after the completion of the research. The use of pseudonyms, without the masking of other identifiers, would provide such protections.

J: So where does this leave us? It seems apparent that there are very real scientific costs introduced when the ethnographer engages in masking, costs that negatively impact the community of scholars by impeding our efforts to construct cumulative social science. It also appears that the reason ethnographers usually give for masking—confidentiality—often does not hold up in practice. Yet I can see that some degree of masking may be practically or ethically necessary for some fieldwork.

My own conclusion is that masking is no longer defensible as the taken-for-granted default position. My experience with naming in The Global Pigeon, and my frustration with how a previous ethnographer’s decision to mask Williamsport is hampering my research on fracking in the same community, have convinced me that ethnographers should make naming the default, and then mask only to the extent required to ethically carry out your research. Alex, where do you come down on this?

M: This is a question I am still struggling with. I do think we should strive to mask as minimally as possible. And I think to do this we need to have extensive, honest, ongoing conversations with our participants about the costs, benefits, tradeoffs, and limitations of masking. As I work to make these decisions for my own book I am doing just this—going back to my participants as well as other community members and stakeholders to have these discussions. Doing so has been invaluable—they’ve made me aware of concerns around naming and masking that are important to them but that I had not thought of and vice versa. I guess I would say that I don’t think there is a universal answer. Every ethnography poses some distinct ethical issues, and so these decisions have to be made on a case-by-case basis, in consultation with one’s participants. That’s where I stand.

I am glad, though, to be having this conversation; it’s an important one. I definitely think that masking is a practice worth rethinking in light of the issues raised here.

J: This is especially the case in the face of scholarly and public demands for greater data transparency. While ethnographers may be understandably reticent to share their interview transcripts and unfiltered fieldnotes, masking minimally, and only when necessary, is arguably a more practical means of addressing the transparency expectation. It also is likely to have more scholarly utility since it enables researchers to bring other perspectives and sources of data to bear on one’s case study, which is in alignment with the goals for data transparency. At any rate, ethnographers risk marginalization both within and outside the academy if they ignore these concerns.

Alexandra Murphy is in the sociology department and population studies center at the University of Michigan. She studies suburban poverty and transportation insecurity and is co-editor of The Urban Ethnography Reader.

Colin Jerolmack is in the sociology and environmental studies departments at New York University. He is author of The Global Pigeon.

Research ethics when gaining access to organizations. Case study

Original source: “doing qualitative research as if counsel is hiding in the closet

I have also faced challenges when studying political organizations. The most stressful experience so far took place during my research on the experiences of young activists who worked as canvassers, recruiting new members and renewing existing memberships for a number of progressive campaigns. The findings of this study went into my book Activism, Inc. Most of the data used for the book came from open-ended semi-structured interviews with one cohort of young people working on the summer canvass and the participant observations conducted in canvass offices during summer 2003.

Preparing to enter the field for this study involved gaining access to the largest canvassing organization in the United States—The Fund for Public Interest Research—which had never before been the subject of an academic study, and likely never will be again. (I created a pseudonym for the organization in Activism, Inc. because the findings from the research were not very complimentary. Since the organization came out in an article in The Chronicle of Higher Education after the book was published, I named it in subsequent publications.) After many rounds of discussions with the organization and positive support from well-known activists whom I knew from my life before I became a sociologist, the organization agreed to be the setting of my research project. Before going into the field to do participant observation in offices and interview canvassers, however, the organization required that we negotiate a memorandum of understanding that would determine who and what I would gain access to and what I could ask about during my research. After some back-and-forth, the organization and I signed the agreement that stated, “The treatment of the data will be consistent with the protocol outlined by the Columbia University Institutional Review Board (IRB Protocol #02/03-998A).”

Although social scientists frequently complain that the requirements of our universities’ IRBs put unnecessary limitations on social research—particularly for projects that collect little personal data about the research subjects—I found the IRB provided me with a welcome shield with which I could protect my research and my subjects from the organization. Throughout the duration of this project, people from the organization made multiple attempts to get my field notes and interview data. In fact early on in the project, a representative from the organization offered to hide in the closet or surreptitiously turn on the office’s intercom so that she could listen in on my interviews.

Even though we had agreed from the beginning that my data would be kept confidential and both sides had signed the agreement that acknowledged that I would be following the regulations of the IRB, the organization persisted. Thanks to the university’s Human Subjects requirements, however, I was able to respond to these requests by pointing out that my protocol, which is required by the university and was clearly outlined in our agreement, would not permit such activities.

In addition to protecting my subjects, the IRB protected me when the organization threatened to take legal action. Right before Activism, Inc. was published, the organization’s legal team threatened to block the publication of the book (for which they had no legal grounds), stating that I had to turn over all of my data to them before they would approve any publication. Once again, the IRB and my human subjects protocol provided a welcome protection. It’s worth noting that, even though my IRB Protocol was protected through Columbia University, I was still required to hire my own lawyer, which cost me thousands of dollars. After enduring hours of phone calls with lawyers from the University and Stanford University Press to go over the research and my methods, our “legal team” agreed that I had done nothing wrong and the book could be published.

Given these experiences, I now conduct all of my research very carefully—basically doing it as if a corporate counsel is looking over my shoulder every step of the way. Moving forward, qualitative sociologists who study less privileged communities should follow the lead of those of us who have been studying elites and do their work AS IF they’re studying a group with their own legal representation. In other words, we all should treat our field sites as if they are populated by a privileged portion of the population who wield law degrees.

Informed consent in political elites studies. Case study

I stumbled across this article “doing qualitative research as if counsel is hiding in the closet”, a very good example of how a researcher proceed when dealing with research ethics regarding confidentiality and inform consent in such particular studies as “political elites”. When providing a description of the research before the beginning of the interview, researcher hand the “ethical review board” or IRB-approved information sheet about the research and tell them that “nothing they say will be directly attributable to them”. In journalist´s parlance, the interview is “off the record”.

Bellow I have pasted the most significant part:

A lot of my research studies political elites. As such, I am frequently conducting participant observation and open-ended, semi-structured interviews in the halls of the US Congress, offices of various federal agencies, political consultants, lobbying firms, and organizations that aim to represent the public’s interest. In other words, my data are collected from a highly educated group of people, an overwhelming proportion of whom have law degrees. Moreover, most of these offices employ some sort of “corporate” counsel that monitors access—or what I think of as my field site and my research subjects. As a result, I have learned to be extremely careful since these lawyers have made it clear to me on a number of occasions that I can lose access and be booted from my field site at any point.

In the 15 years since I completed my PhD, I have been challenged by research subjects regarding my use of their names or the data I collected from them in two particularly anxiety-inducing cases. In the first, a subject of an interview who worked for a Congressional Committee found a draft of a paper online that directly quoted him. While I was making the final edits on my first book, which named this subject and quoted him directly, I got a very aggressive email from him. In response, I passed on a copy of the transcript of the interview that included an exchange during which I asked if I could use the subject’s name and he affirmed. His concerns were alleviated after receiving the transcript that included his consent. Nonetheless, I removed direct reference to this research subject in my book. I also adapted the way that I approach political elites whom I study.

Although these interviews are usual seen as exempt from IRB requirements because I am asking about subjects’ political work and not anything personal, I have found I get better data (and avoid such interactions with JDs working in the political arena) if I grant all subjects confidentiality. When providing a description of my research before I begin an interview, I hand my subjects an IRB-approved information sheet about the research and tell them that nothing they say will be directly attributable to them. In journalists’ parlance, the interview is “off the record.” I state that I will email them directly for approval if I find there is any segment that I would like to quote directly in my work. Because so many of my subjects have experience speaking with journalists, I find that following similar norms about attribution puts the subjects at ease. Although this process adds some work when I am writing, it tends to yield more interesting data. This process also gives me an electronic trail if I am approached by subjects post hoc, which can be very helpful if I am contacted by lawyers.

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!

Regretting Motherhood: A Sociopolitical Analysis

Based on in-depth interviews with twenty-three Israeli mothers, this article seeks to contribute to an ongoing inquiry into women’s subjective experiences of mothering by addressing an understudied maternal emotive and cognitive stance: regretting motherhood. The literature teaches us that within a pronatal monopoly, threatening women that they will inevitably regret not having children acts as powerful reproducer of the ideology of motherhood. Simultaneously, motherhood is constructed as a mythical nexus that lies outside and beyond the human terrain of regret, and therefore a desire to undo the maternal experience is conceived as an object of disbelief. By incorporating regret into maternal experiences, the purpose of the article is twofold: The first is to distinguish regret over motherhood from other conflictual and ambivalent maternal emotions. Whereas participants’ expressions of regretting motherhood were not bereft of ambivalence, and thus were not necessarily exceptional or anomalous, they foreground a different emotive and cognitive stance toward motherhood. The second purpose is to situate regret over motherhood in the sociopolitical arena. It has been suggested that the “power of backward thinking” might be used to reflect on the systems of power governing maternal feelings in two ways: first, through a categorical distinction in the target of regret between object (the children) and experience (maternity), which utilizes the cultural structure of mother love; second, by opposing the very essentialist presumption of a fixed female identity that naturally befits mothering or progressively adapts to it and evaluates it as a worthwhile experience.

Donath, O. (2015). Regretting motherhood: A Sociopolitical analysis. Signs,40(2), 343-367.

Focusing research topic in six steps

In previous post I have addressed different stages of the research process, that is, from the very beginning when one is formulating the research question up to the final conclusions. However, this post aims to dig into the first stages any researcher is coping at the beginning and, particularly, non-experienced researchers. Having a consistent research question is probably the most critical and challenging part. Having a good question is probably the best way to better orientate you in the subsequent stages. It works as a lighthouse that avoids disorientation in the sometimes long and confusing research process. And this is because it allows us to distinguish between relevant and non relevant data. The criterion is very simple: “you must select from all data you find just those data that support an answer to a question” (Booth et al., 2003)

What are the results of having ambiguous or abstract question? Basically, selecting data can be frustrating, so many sources, so many information and a lot of doubts of what is and not important.

So, the question is how to raise a good research question? What is more, how to raise a research question that is not merely interesting but also has wider significance, in this case, for the discipline of economics. In other words, does your question solve any problem someone, for instance, other researchers, think needs to be solved? Or, on the contrary, your question only intrigues you: “why do cats rub their faces against us? And here is when many beginners fail when formulating a research. They are unable to formulate a “big” question but with a “mental itch” (Op cit.) that only one researcher feels the need to scratch.

To that end, you must follow the following process: identify your interest-find a topic-research problem:

  1. Identifying your research interest.

Start by listing two or three interests that you´d like to explore. Interest means something that is important for you, so that you would like to know better. A research interest is something that arouses our curiosity. Sometimes without really knowing why and sometimes because they are linked to those categories that define us as person: the place you are from or you live, your hobbies, your family, your gender, nationality, your aspirations in life etc. A research interest is something that arouses our curiosity, something.

2. From an interest to a topic.

Identifying interest is seldom a problem faced by researchers, not even beginners. Most of the people have plenty of interests to pursue. However, the first challenge is often to locate a good research topic among all interests. To make it clear: a research topic is basically an interest enough focused for you to become an expert on it or, at least, to make you know much about it than you do now. Ideally, you should go for what interests you most. As suggested by Booth et al (2003:41) “nothing contributes to the quality of your work more than your commitment to it. Think in previous subjects throughout your graduate. Is there any subject where your grades have pointed out? Which one have you enjoyed most? Have you ever performed a remarkable work on a specific discipline or academic area? You might also try to identify an interest based on work you are doing or will do in a different course. Finally, do not hesitate to discuss your ideas with someone else. Get rid of your fears and shame and talk friends and classmates. It will be helpful to shape your idea and make it feasible.

If you are still stuck, you can find help on the Internet or Faculty library. The internet may seem the easiest way, but that can be also frustrating due to the overwhelming amount of information, especially if you have entire freedom to choose the topic. You should start by visiting your library or the social profile of some of your professors. For instance, you can join for free some academic network as ResearchGate and look at the work made by some of them. Starting by checking out the work of faculty member allow you to contact them directly in case you want to ask specific questions or material. That may also contribute to a better knowledge transference between professors and students and, hence, creating a more active and vibrant local intellectual life.

If you have already an idea for a topic you can search for relevant literature by keywords. Imagine you are interested in local economic development. If you scan this term on the internet, you will find thousands of references. Don´t read randomly; start with entries in a general encyclopaedia as Wikipedia. The fact you topic has some entries is a good sign. It means that you are not the only one working on this topic. Have a look to the main literature references given in the encyclopaedia entry in order for you to identify the main authors. Then you can look at entries in a more specialized search engine. For instance, Google Scholar. Here the search is focused on academic papers, excluding those performed in industry. Finally, check out specialized journals. Once again, if your topic is local economic development, then look for a journal specialized on this area. Read a reasonable amount of articles or papers related to your specific topic. Do not hesitate to take a single paper as reference. What is more, it is highly recommendable to use one paper as a guide for your own research. Your aim could perfectly be reproducing the same study but adding new elements and taking care of not committing plagiarism.

  1. From a broad topic to a focused one.

At this point, you risk settling on a topic so broad that could perfectly be a heading in a encyclopaedia: “local economic development”, “regional development”. A topic is usually too broad if you can state it in four or five words: “Local development problems in Poland”.

You can narrow this topic by adding words and phrases, but of a special kind: description, contribution, analysis, etc. All of them are derived from verbs expressing actions or relationships: to describe, to contribute, to analyse. Without such words, your topic is a static thing. But when you use nouns derived from verbs, you move your topic a step closer to a claim that your readers might find significant.

Note what happens when these topics become statements.

TOPIC                                                                                                                 CLAIM

Economic development

Poland has experienced one of the most notable economic growths in Europe in the last decade


  1. From a focused topic to questions.

A very common mistake among beginners is rushing from a topic to the “data dump”. Having a promising topic does not mean to have done all we need to get started with data collection. “Poland economic growth since joining European Union” is, indeed, a good topic. You can accumulate economic data on this topic, the evolution of the different indicators and differences between regions. This might be enough to have a good grade at high school, because you show that you can focus on a topic, find data on it, and assemble those data into a report. This is not a small achievement after all. However, in any advance course, as this at the university, such report falls short because it offers only random bits of information. Readers of significant report do not only want information. As suggested by Booth et al. (2003), they also want “answer to question worth asking”. To be fair, those who are fascinated with a particular topic frequently feel like any information is worth reading for its own sake. Advance researchers, however, do not report data for their own sake, but to support the answer to a question that they and their readers think is worth asking.

The best form to identify what you do not know about a topic is to barrage it with questions. First of all, the most predictable questions within you field, usually journalistic questions like headed by interrogative particles as who, what, when and where. They usually raise way to descriptive reports, that is, they may ask only about matters of settled fact. Then you can focus on how and why headed questions. They are more likely to invite deeper research and lead to more interesting answers.

Finally you can ask four kinds of analytical questions:

  1. About composition: how is the topic part of a larger system? For instance, what factors explain the better economic growth performance in Poland in comparison to other new European Union members? What industries have contributed most to such growth? Does the economic growth mean a loss of local embeddings?
  2. About the history: how the growth developed since 2005? Is it possible to identify different stages? How different industries have developed since 2005? How economic growth has affected demography and immigration?
  3. Categorization: Identify its characteristics and the categories that include it: How the economic growths vary from one region to another? How does it from one industry to another?

Once you have a clear question you may stop brainstorming. The most important aim is to identify a question that really arouses your intense curiosity. Discuss your idea with someone. It will be helpful to shape your idea and make it feasible. Pose your question in a network as Research Gate to test others opinion. Having no answer might be an indicator of either the question is not correctly formulated, or the question has no significance for your field.

  1. From a merely interesting question to its wider significance.

Once you have a question that grabs your interest, you must pose a tougher question: why should this question also grab my readers? What makes it worth asking? It is not easy to guess what will eventually interest your readers. Booth et al. Suggest working toward an answer in three steps:

  1. Describe your topic in a sentence as specific as you can make it:

“I am trying to learn about (working on, studying) _____________________

  1. Add to that sentence and indirect question that specifies something that you do not know or understand about your topic but want to:

“I am trying to learn about (working on, studying) _____________________ because I want to find out who/what/when/where/whether/why/how________________________________

I you success to compose a good sentence at this point, you are moving yourself beyond the kind of aimless collection and reporting of data that afflicts too much research.

  1. Motivate your question. This is probably the most challenging step. But this step indicates whether your question is not just interesting to you but possibly significant to others. To do that, add another indirect question, a bigger and more general one that explains why you are asking your first question. Introduce this second implied question with in order to help my reader understand how, why, or whether:

“I am trying to learn about (working on, studying) _____________________ because I want to find out who/what/when/where/whether/why/how________________________________in order to help reader to understand how, why, or whether________________________

If that larger question touches issues important for your field and/or are current and controversial topics nowadays, then you have motives to consider that your readers should care about its answer to the question you are posing.

Experienced researchers are able to flesh out this whole process even before they start the data collection, basically because they are working on a well-known question, i.e. a widely investigated problem that others in their field are already interested in. Actually, advanced researchers often begin their research with questions that others have asked before but not answered thoroughly or maybe even correctly. Hence, your research question could be the result of not only the exploration of new significant topics, but just the continuation of the work started by other researchers.

Finally, the truth is that many researchers, including advanced ones, find that they can´t flesh out these steps until they´re nearly finished. In other words, many researchers write up the results without having thought through these steps at all. It means that at the beginning of the project you may not be able to get past these three steps, but it is important you regularly reflect on them throughout the whole research project. Then you will know where you are and where you still have to go.

To summarize, your aim is to explain:

  1. What you are writing about-your topic: I am studying…
  2. What do don´t know about it- your question: because I want to find out…
  3. Why you want your reader to know about it-your rationale: in order to help my reader understand better…

6. From questions to problems.

Having a good question is usually a synonymous of addressing a research problem. But what a research problem really is. We first should distinguish between practical problems and research problems. Everyday research usually begins with solving practical problems that has just landed on you, a problem that left unresolved, means trouble. We all have this kind of problems and we all are often able to solve or, at least, we can figure out the way it may be solved. However, whenever the solution of such problem is not obvious, (i.e. when you ask yourself questions that you can´t answer), then you need to solve first a problem of another kind, a research problem defined by what you do not know or understand and; so that then you can address the practical problem.

So the process of addressing a practical problem is familiar for everyone:

PRACTICAL QUESTION: My brakes have started screeching?

RESEARCH QUESTION: Where can I get them fixed right away?

RESEARCH PROBLEM: Find the yellow pages and look up closest brake shop.

RESEARCH ANSWER: The Car shoppe, 1401 East 55th Street.

APPLICATION: Call to see when they can fix them.

Graphically, the relationship between practical and research problems looks like this:

** It is very important distinguish between Practical problems and research problems.

Although solving a practical problem usually requires that we solve a research problem as well, there are differences between them:

– A practical problem is caused by some condition in the world, from e-mail spam to terrorism, that makes us unhappy because it costs us time, money, respect, security, pain, even our lives. You solve a practical problem by doing something that changes the world by eliminating the causes that lead to its costs, or by encouraging others to do so.

– A research problem is motivated not by palpable unhappiness, but by incomplete knowledge or flawed understanding. You solve it not by changing the world but by understanding it better.

At this point you may have notice that the term problem has a special meaning in the world of research. In our everyday world, a practical problem is something we try to avoid. But in the academic world, a research problem is something we eagerly seek out, even inventing one, if we have to.

** Distinguishing “Pure” and “Applied” Research.

Having a practical problem is not necessary the point of departure when formulating a research problem. In other words, you can try to solve a research problem without having a practical problem or, at least, not apparently. Hence you want to address a research problem due to the interest of a community of researchers. This research is called pure. But when the research is rooted in a practical problem, that is, it is the practical problem that encourage to do a research, then we call this applied research. You can tell whether a research problem is pure or applied by looking at the last of the three steps in defining your project. Does it refer to knowing or doing?


“I am trying to learn about (working on, studying) _____________________ because I want to find out who/what/when/where/whether/why/how________________________________in order to understand how, why, or whether________________________


“I am trying to learn about (working on, studying) _____________________ because I want to find out who/what/when/where/whether/why/how________________________________so that policy makers can use data to implement new employment projects________________________

Is it useful pure research?

Well, the truth is that most research projects in the humanities and many in the natural and social sciences have no direct application to daily life. In fact, as the word pure suggests, many researchers value pure research more highly than they do applied. They believe that the pursuit of knowledge “for its own sake” reflects humanity´s highest calling-to know more and understand better, not for the sake of money or power, but for the good that understanding itself brings. What is more, the fact one project has no practical application usually means that the application is not immediately. But the truth is that many pure research results end up having important impact on society. For instance, the recent discovery of gravitational waves has a priori no application. However, it is well known that this will impact the way we understand universe and humanity, as well as other discoveries did in the past.

Finally, a typical beginner´s mistake is getting not content with having no significant practical problem so they try to force their project into the practical domain. That´s usually a mistake because no one can solve the world´s great problem in a five- or even a fifty-page paper. But a good researchers might help us understand those problems better, which get us closer to the solution.