Blogging as analytical aid for team-based research projects

Research notes have traditionally played an important role in the analysis of data in social science. Apart from transcribing audio-recording, the contextual information serves as a rich source of complementary data. Indeed, various researchers have suggested additional ways of recording supplementary information (Miles and Huberman 1994). These include “interim summaries”, “self-memos”, “and researcher´s diary”. Yet, most of them are usually presented as offline analytical aids and frequently for individual based analysis process. Social media, however, has redimensioned these tools and make them useful for team-based research projects, particularly for multisite and cross-national projects. The fact of publishing your research notes and summaries contribute may encourage both theoretical and methodological discussions during the research process:

  1. Online interim summaries: as the analysis progress, different team members may wish to write an “interim summary” of the progress to date (Saunders, 2011). What you have found so far; what level of confidence you have in your findings and conclusions to date; what you need to do in order to improve the quality of your data and/or to seek to substantive your apparent conclusions, or to seek alternative explanations; how you will seek to achieve the needs identified by the above interim analysis.
  2. Online self-memos. Self memos allow to record ideas that occur to you about any aspect of your research, as you think of them. Where you omit to record any idea as it occurs to you it may well be forgotten. Self memos may vary in length from a few words to one or more pages. They can be written as simple notes and they do not need to be set out formally. The occasions when you are likely to want to write a memo include (Saunders, 2011):
    1. when you are writing up interview or observation notes, or producing a transcript of this event;
    2. when you are constructing a narrative;
    3. when you are categorizing these data;
    4. as you continue to categorize and analyze these data;
    5. when you engage in writing your research project.

Furthermore, the openness of the methodology beyond team members may encourage a more dynamic relationship between research and the general public, which is consistent with the idea of science suggested by Nowotny et al. in the book “Re-thinking science”. In it, the authors argue that changes in society now make such communications both more likely and more numerous, and that this is transforming science not only in its research practices and the institutions that support it but also deep in its epistemological core.



Glaser, B. G. (1978). Theoretical sensitivity: Advances in the methodology of grounded theory. Sociology Pr.

Huberman, M., & A AND M MILES, B. (1994). Data management and analysis methods. Handbook of Qualitative Research. N. Denzin and Y. Lincoln London.

Nowotny, H., Scott, P., & Gibbons, M. (2001). Re-thinking science: Knowledge and the public in an age of uncertainty (p. 12). Cambridge: Polity.

Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India.

“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.

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.

Donald Trump discourse/language analysis

Black-and-white highlights the social dimension of urban photography, Ouburg suggests


Ouburg, photographer who prefers photographing “other people above all”. I like the way he expresses why he has predilection for black-and-white photos.

In many occasions, colour distracts the spectator´s attention while black-and-white make it easier to concentrate on the topic.

Although he doesn´t discard colour provided that it adds something to the image.

Source and more photos [spanish]

El enfoque semiológico en el análisis sociológico

La peculiaridad del enfoque semiológico responde al siguiente interrogante: “¿Por qué y cómo en una determinada sociedad algo —una imagen, un conjunto de palabras, un gesto, un objeto, un comportamiento, etc.— significa?


Magariños de Morentin, Juan Angel (1996). Los fundamentos lógicos de la semiótica y su práctica. Buenos Aires: Edicial.