Intersections: Women’s and Gender Studies in Review Across Disciplines call for submissions

Intersections: Women’s and Gender Studies in Review Across Disciplines has just published its ninth issue. Earlier this month, four current editorial staff members, Amy Lodge, Michelle Mott, Vivian Shaw, and Maggie Tate, hosted a round table discussion about working on an interdisciplinary journal. At the round table, the editors discussed the process for crafting an interdisciplinary call for papers, the procedure for producing the journal from the call for papers to the publication, and the move from a print journal to a web-based journal.

Intersections was founded in 2002 by graduate students in the English Department and the Center for Women’s and Gender Studies. Over the last several years, a number of Sociology graduate students have served as editorial staff members, contributors, and peer-reviewers. The current staff also consists of graduate students from the Center for Women’s and Gender Studies, Radio-Television-Film, American Studies, and African and African Diaspora Studies. As Amy, Michelle, Vivian, and Maggie walked us through the CFP for Issue 9: Gender and Social Justice and for the current CFP for Issue 10: Media(ting) Genders and Sexualities: Identity, Representation, and Politics in Media, they discussed how the editorial board works to find language that is broad enough to attract a wide array of submissions, but is specific enough to articulate a general theme. Choosing key terms that both reflect the editorial board’s interests and speak across many disciplines (recognizing that certain terms take on different meanings within various scholarly fields) is very challenging.

The current issue and last two issues are available in print copy (at no cost). You can obtain a copy by emailing: In addition, the current issue is available to view online at: The Intersections Editorial Board are accepting submissions for article abstracts, book reviews, and creative submissions until December 1, 2011. See Call for Papers below for details:

CFP: Media(ting) Genders and Sexualities: Identity, Representation, and Politics in Media
Intersections: Women’s and Gender Studies in Review Across Disciplines is an interdisciplinary graduate student publication welcoming work from current graduate students. We are committed to the interdisciplinary research of women’s and gender issues and are affiliated with the Center for Women’s and Gender Studies at the University of Texas at Austin.

The journal encourages scholars in all fields to contribute scholarly essays, book reviews, and creative writing relating to this issue’s theme, Media(ting) Genders and Sexualities: Identity, Representation, and Politics in Media. We expect that this theme will inspire submissions that put gender and sexuality in conversation with intersecting identities of race, economic class, disability, nationality, and indigeneity, and encourage submissions on all forms of media.
Submissions might address, but are not limited to, the following topics:

● Representations of gender, sexuality, and race
● Property, authorship, and expression in local and transnational contexts
● Queering media
● Space and the body in media
● Social media and popular culture

The deadline for 200 – 300 word abstracts is December 1, 2011. We use a digital Open Journal System for submissions. To submit your abstract, please make an account on our website: You will be able to track your submission through your account. Questions should be sent to editors at
Completed papers and artwork are due by February 1, 2012. All submissions should include the author’s name, institution and department, contact information, title of submission, and word count. Scholarly essays and creative writing should be less than 5000 words.  For book reviews, please email for a list of possible titles. Book reviews should be between 750 –1250 words and include publication information about books reviewed.

Screw the Models: A Talk on Data Dilemmas with Professor Alex Weinreb

Last week on Wednesday, 9 November, Professor Alex Weinreb gave a fascinating talk to an audience of graduate students and professors from the Department of Sociology here at UT Austin.

Professor Weinreb’s talk, entitled “Screw the Models, get back to the data: Or, on the disciplinary dangers of data ex nihilo” comes out of research he has been doing for his current book project on the mis-measurement of society.

The basic premise of Weinreb’s talk, which has potentially earth-shattering implications for the positivistic social sciences, is that there are manifold errors at the basic level of data collection, particularly in the third world, which may lead to mistaken results in quantitative studies that rely on survey-based research.

Weinreb contends that the past four or five decades of quantitative research have witnessed an impressive growth in the complexity of statistical modeling techniques, and in particular post-facto techniques for “data cleaning” that attempt to fix problems in survey data prior to analysis. Yet, since the 1950s, there has been little social science research aimed at assessing survey errors in the third world and finding better ways to get more accurate data.

He gave several shocking examples of how survey research has missed big conclusions due to data issues, despite fancy models. First, heavy-weight demographers in the 1980s completely missed the process of African fertility transitions, which was happening as they wrote, because their data were not adequate to the task they proposed. Second, a multi-million dollar cross-national survey of several Asian countries in the 1990s was unable to find any significant results regarding women’s autonomy, which contrary to theoretical assumptions seemed to be greater in patrilineal and patriarchal areas than in others.

In sum, whether social scientists miss something big, or are looking for something big and can’t measure it, the answers to both of these errors lie in the data, rather than in more complex models. And the essence of these errors lie in “non-sampling error”. In other words, even where sampling is perfectly random, or adjusted with appropriate weights, a number of other errors continue to creep into datasets. The shocking thing is that non-sampling error accounts for the majority of variance in most data.

Some types of errors that are commonly seen in third world surveys include variations in results due to translation issues, insider-outsider dynamics, male-female interviewer-interviewee dynamics, and privacy issues (whether or not a third party is present during the interview).  Some of Weinreb’s recent work in the Dominican Republic has shown the variation in results when interviewers know the respondent personally, are an unknown community insider, or are an outsider to the community. In one illustrative example, respondents were much more likely to falsely claim to know a fictitious person among a list of real personnages when interviewed by an outsider, something Anthropologists and ethnographers call “sucker bias.” But the problem is that the directionality of any such bias is not consistent. On one set of questions respondents may be more likely to give accurate answers to outsiders than insiders (or to men rather than women), and vice versa for another set. And in another country or part of the same country, or even among different gender and age groups, this situation may be completely different.

There are clearly no easy solutions for these data dilemmas. But further research into data collection methods is one key to improving results. Although there have been advances in data collection methods in the developed world, with regards to the third world, this type of research has stalled since the 1950s and 1960s after World Fertility Surveys in the 1970s, and later Demographic & Health Surveys from the 1980s until today became the nearly universal gold standard for survey research. Having one such standard method for survey research does have the benefit of comparability across place and time. However, it seems to have serious problems of accuracy since it does not get the best results in all contexts. In other words, the current position of the social science academy is to privilege reliability of data over validity for a number of reasons, including comparability and tradition.

Following his talk, a number of graduate students and professors engaged in a lively discussion with Weinreb, parsing out the details of some of his broader brush strokes, and debating the pro and contra of some of his hypotheses. Department Chair and Professor Christine Williams pointed out that many of these data dilemmas were critiques often leveled by qualitative researchers at quantitative research in general, but noted that it was important to see this type of nuanced discussion from within a quantitative framework, since it is essential to always improve all of our research methods. Professor Pam Paxton, alluded to the conversation from the week before at the brown bag presentations of graduate students Amanda Stevenson and Isaac Sasson, pointing out that there are a number of solutions to data problems, even issues of non-sampling error, if researchers take the time to thoroughly diagnose problems and deal with them. She also pointed out that there is an accountability mechanism built into this type of survey research in the form of policies and programs, which are often informed by such social science research and ultimately prove successful or unsuccessful.

Isaac Sasson turned the discussion toward the future of the field and wondered aloud about how these ideas affect the big picture of the knowledge of structure and the structure of knowledge. And graduate student Marcos Perez ruminated about interdisciplinary linkages and the ways in which some of these issues could be solved through collaboration with colleagues in other departments.

Although we don’t yet have the answers to a number of these questions, Professor Weinreb’s work did shed some light on the problems of data assumptions ex nihilo (out of nothing), which ignore non-sampling error. Given the entrenched nature of quantitative research traditions, this is likely to be but a quiet revolution in the social sciences in the immediate future, but a revolution nonetheless, and one to keep our eyes on.

Letisha Brown wins Outstanding Paper Award at NASSS

Graduate student Letisha Brown received the Barbara A. Brown Outstanding Student Paper Award in the master’s students section of the North American Society for the Sociology of Sport, for her paper “The Spectacle of Blackness: Race, Representation and the Black Female Athlete.”

The NASSS annual conference titled “Revolutionary Sporting Bodies: Technologies in Practice” this year took place in Minneapolis, Minnesota. Papers winning the award are typically published in the flagship journal of NASSS, the Sociology of Sport Journal, and many former winners have gone on to become leading figures in the sociology of sport.

Kudos to Letisha!

Addenda errata, or, Toward a sociology without society

In ‘What’s in an Error? A Lévy Walk from Astronomy to the Social Sciences’ Isaac talked about how it was really error, or more precisely, the idea and observation that errors in natural scientific experiments and measurements seem to exhibit certain repeatable properties, or laws, that formed the foundation of the study of probability and statistics. Only against a background of noise, variance and aberrations was a concept of normal (eg average man), as well as the idea of truth as non-error, able to emerge and take shape. Versions of these concepts remain central to the social sciences from the 18th century to this day.

Alex Weinreb brought up the point that the rise of statistics and its incorporation into social studies were coeval with the relative geographic immobility of people in the 18th century. What struck me was how much statistical sociology is tied to criminology since its inception. Adolphe Quetelet, the founder of statistical sociology, was a criminologist and used his method primarily to study crime causation. Even the Lévy walk was a mathematical concept, I believe, first developed out of practical application to track down prison escapees within certain calculated perimeters. Given its strong ties to Staatswissenschaft, the emergence of social statistics seems to go hand in hand with that of governance and social control, policy and police–hence the centrality of the normal-pathological distinction.

Nonetheless, the historical contingency of something doesn’t necessarily invalidate its internal consistency. Statistics does describe something, and presents reality, at least in part, in certain ways. Amanda’s presentation outlined some of these principles or consistencies and addressed the utilities and limitations, risks and yields, of a number of statistical models (eg instrumental variables). Alex pointed out that current multilevel nonlinear social statistical models even seem to vindicate many previous, non-statistics-based sociological observations. The underlying assumption in the debate on merits of statistics-based sociology versus those of non-statistics-based sociology is interesting, in that proponents typically put forth that what can’t be empirically verified can’t be included as true, while opponents counter what’s true often lies beyond empirical verification itself. The positions perhaps are not so contradictory as they seem, for there is a supposition common to both, and that is, large-scale phenomena are necessarily somehow more complex than small-scale phenomena (if the distinction of large and small even holds). Here, the statistician’s or (for the lack of a better term) ‘positive sociologist’s’ role becomes merely one of delimitation, whereas that of the ‘critical sociologist’ becomes one of extension of epistemic scope. Expansion and edification are not mutually exclusive.

Perhaps it is this very assumption that needs questioning. Is it really easier to predict the motion of a cell or atom than it is to predict how someone or group will behave? Physics has shown us that the opposite can actually be the case. Large-scale phenomena, as such, are to a far extent stable and relatively easily predictable; it’s when we get down to the micro- and nano-levels of reality that laws collapse and things become very uncertain. Light may be both particle and wave, and yet this keyboard on which I’m typing, I’m fairly certain, won’t suddenly turn into a dove and fly away.

Sociologist Jean Baudrillard once said that knowledge is a high-definition screen onto which the low-definition image that is reality is projected. What may this mean for the sociological apparatus? How may the relation between theory and evidence, knowledge and object, itself be re-conceived within the field? Amidst such questions, Isaac’s and Amanda’s talks remind us of a level of reflexivity that is both essential and useful to the practice and imagination of sociology.