Methodology will only get you so far

I’ve been working on a post about humility as an organizational strategy. This is not that post, but it is also about humility.

I like to think of myself as a research methodologist, because I’m more interested in research methods than any specific area of study. The versatility of methodology as a concentration is actually one of the biggest draws for me. I love that I’ve been able to study everything from fMRI subjects and brain surgery patients to physics majors and teachers, taxi drivers and internet activists. I’ve written a paper on Persepolis as an object of intercultural communication and a paper on natural language processing of survey responses, and I’m currently studying migration patterns and communication strategies.

But a little dose of humility is always a good thing.

Yesterday I hosted the second in a series of online research, offline lunches that I’ve been coordinating. The lunches are intended as a way to get people from different sectors and fields who are conducting research on the internet together to talk about their work across the artificial boundaries of field and sector. These lunches change character as the field and attendees change.

I’ve been following the field of online research for many years now, and it has changed dramatically and continually before my eyes. Just a year ago Seth Grimes Sentiment Analysis Symposia were at the forefront of the field, and now I wonder if he is thinking of changing the title and focus of his events. Two years ago tagging text corpora with grammatical units was a standard midstep in text analysis, and now machine algorithms are far more common and often much more effective, demonstrating that grammar in use is far enough afield from grammar in theory to generate a good deal of error. Ten years ago qualitative research was often more focused on the description of platforms than the behaviors specific to them, and now the specific innerworkings of platform are much more of an aside to a behavioral focus.

The Association of Internet Researchers is currently having their conference in Denver (#ir14), generating more than 1000 posts per day under the conference hashtag and probably moving the field far ahead of where it was earlier this week.

My interest and focus has been on the methodology of internet research. I’ve been learning everything from qualitative methods to natural language processing and social network analysis to bayesian methods. I’ve been advocating for a world where different kinds of methodologists work together, where qualitative research informs algorithms and linguists learn from the differences between theoretical grammar and machine learned grammar, a world where computer scentists work iteratively with qualitative researchers. But all of these methods fall short because there is an elephant in the methodological room. This elephant, ladies and gentleman, is made of content. Is it enough to be a methodological specialist, swinging from project to project, grazing on the top layer of content knowledge without ever taking anything down to its root?

As a methodologist, I am free to travel from topic area to topic area, but I can’t reach the root of anything without digging deeper.

At yesterday’s lunch we spoke a lot about data. We spoke about how the notion of data means such different things to different researchers. We spoke about the form and type of data that different researchers expect to work with, how they groom data into the forms they are most comfortable with, how the analyses are shaped by the data type, how data science is an amazing term because just about anything could be data. And I was struck by the wide-openness of what I was trying to do. It is one thing to talk about methodology within the context of survey research or any other specific strategy, but what happens when you go wider? What happens when you bring a bunch of methodologists of all stripes together to discuss methodology? You lack the depth that content brings. You introduce a vast tundra of topical space to cover. But can you achieve anything that way? What holds together this wide realm of “research?”

We speak a lot about the lack of generalizable theories in internet research. Part of the hope for qualitative research is that it will create generalizable findings that can drive better theories and improve algorithmic efforts. But that partnership has been slow, and the theories have been sparse and lightweight. Is it possible that the internet is a space where theory alone just doesn’t cut it? Could it be that methodologists need to embrace content knowledge to a greater degree in order to make any of the headway we so desperately want to make?

Maybe the missing piece of the puzzle is actually the picture painted on the pieces?

comic

Planning a second “Online Research, Offline Lunch”

In August we hosted the first Online Research, Offline Lunch for researchers involved in online research in any field, discipline or sector in the DC area. Although Washington DC is a great meeting place for specific areas of online research, there are few opportunities for interdisciplinary gatherings of professionals and academics. These lunches provide an informal opportunity for a diverse set of online researchers to listen and talk respectfully about our interests and our work and to see our endeavors from new, valuable perspectives. We kept the first gathering small. But the enthusiasm for this small event was quite large, and it was a great success! We had interesting conversations, learned a lot, made some valuable connections, and promised to meet again.

Many expressed interest in the lunches but weren’t able to attend. If you have any specific scheduling requests, please let me know now. Although I certainly can’t accommodate everyone’s preferences, I will do my best to take them into account.

Here is a form that can be used to add new people to the list. If you’re already on the list you do not need to sign up again. Please feel free to share the form with anyone else who may be interested:

 

Rethinking Digital Democracy- More reflections from #SMSociety13

What does digital democracy mean to you?

I presented this poster: Rethinking Digital Democracy v4 at the Social Media and Society conference last weekend, and it demonstrated only one of many images of digital democracy.

Digital democracy was portrayed at this conference as:

having a voice in the local public square (Habermas)

making local leadership directly accountable to constituents

having a voice in an external public sphere via international media sources

coordinating or facilitating a large scale protest movement

the ability to generate observable political changes

political engagement and/or mobilization

a working partnership between citizenry, government and emergency responders in crisis situations

a systematic archival of government activity brought to the public eye. “Archives can shed light on the darker places of the national soul”(Wilson 2012)

One presenter had the most systematic representation of digital democracy. Regarding the recent elections in Nigeria, he summarized digital democracy this way: “social media brought socialization, mobilization, participation and legitimization to the Nigerian electoral process.”
Not surprisingly, different working definitions brought different measures. How do you know that you have achieved digital democracy? What constitutes effective or successful digital democracy? And what phenomena are worthy of study and emulation? The scope of this question and answer varies greatly among some of the examples raised during the conference, which included:

citizens in the recent Nigerian election

citizens who tweet during a natural disaster or active crisis situation

citizens who changed the international media narrative regarding the recent Kenyan elections and ICC indictment

Arab Spring actions, activities and discussions
“The power of the people of greater than the people in power” a perfect quote related to Arab revolutions on a slide from Mona Kasra

the recent Occupy movement in the US

tweets to, from and about the US congress

and many more that I wasn’t able to catch or follow…

In the end, I don’t have a suggestion for a working definition or measures, and my coverage here really only scratches the surface of the topic. But I do think that it’s helpful for people working in the area to be aware of the variety of events, people, working definitions and measures at play in wider discussions of digital democracy. Here are a few question for researchers like us to ask ourselves:

What phenomenon are we studying?

How are people acting to affect their representation or governance?

Why do we think of it as an instance of digital democracy?

Who are “the people” in this case, and who is in a position of power?

What is our working definition of digital democracy?

Under that definition, what would constitute effective or successful participation? Is this measurable, codeable or a good fit for our data?

Is this a case of internal or external influence?

And, for fun, a few interesting areas of research:

There is a clear tension between the ground-up perception of the democratic process and the degree of cohesion necessary to affect change (e.g. Occupy & the anarchist framework)

Erving Goffman’s participant framework is also further ground for research in digital democracy (author/animator/principal <– think online petition and e-mail drives, for example, and the relationship between reworded messages, perceived efficacy and the reception that the e-mails receive).

It is clear that social media helps people have a voice and connect in ways that they haven’t always been able to. But this influence has yet to take any firm shape either among researchers or among those who are practicing or interested in digital democracy.

I found this tweet particularly apt, so I’d like to end on this note:

“Direct democracy is not going to replace representative government, but supplement and extend representation” #YES #SMSociety13

— Ray MacLeod (@RayMacLeod) September 14, 2013

 

 

Language use & gaps in STEM education

Today our microanalytic research group focused on videos of STEM education.

 

Watching STEM classes reminds me of a field trip a fellow researcher and I took to observe a physics class that used project based learning. Project based learning is a more hands on and collaborative teaching approach which is gaining popularity among physics educators as an alternative to traditional lecture. We observed an optics lab at a local university, and after the class we spoke about what we had observed. Whereas the other researcher had focused on the optics and math, I had been captivated by the awkwardness of the class. I had never envisioned the PJBL process to be such an awkward one!

 

The first video that we watched today involved a student interchangeably using the terms chart and graph and softening their use with the term “thing.” There was some debate among the researchers as to whether the student had known the answer but chosen to distance himself from the response or whether the student was hedging because he was uncertain. The teacher responded by telling the student not to talk about things, but rather to talk to her in math terms.

 

What does it mean to understand something in math? The math educators in the room made it clear that a lack of the correct terminology signaled that the student didn’t necessarily understand the subject matter. There was no way for the teacher to know whether the student knew the difference between a chart and a graph from their use of the terms. The conversation on our end was not about the conceptual competence that the student showed. He was at the board, working through the problem, and he had begun his interaction with a winding description of the process necessary (as he imagined it) to solve the problem. It was clear that he did understand the problem and the necessary steps to solve it on some level (whether correct or not), but that level of understanding was not one that mattered.

 

I was surprised at the degree to which the use of mathematical language was framed as a choice on the part of the student. The teacher asked the student to use mathematical language with her. One math educator in our group spoke about students “getting away with fudging answers.” One researcher said that the correct terms “must be used,” and another commented about the lack of correct terms as indication that the student did “not have a proper understanding” of the material. All of this talk seems to bely the underlying truth that the student chose to use inexact language for a reason (whether social or epistemic).

 

The next video we watched showed a math teacher working through a problem. I was really struck by her lack of enthusiasm. I noticed her sighs, her lack of engagement with the students even when directly addressing them, and her tone when reading the problem from the textbook. Despite her apparent lack of enthusiasm, her mood appeared considerably brighter when she finished working through the problem. I found this interesting, because physics teachers usually report that their favorite part of their job is watching the students’ “a-ha!” moments. Maybe the rewards of technical problem solving are a motivator for both students and teachers alike? But the process of technical problem solving itself is rarely as motivating.

 

All of this leads me to one particularly interesting question. How do people in STEM learning settings distance themselves from the material? What discursive tools do they use? Who uses these discursive tools? And does the use of these tools change over time? I wonder in particular whether discursive distancing, which often parallels female discursive patterns, is more common among females than males as they progress through their education? Is there any kind of quantitative correlate to the use of discursive distancing? Is it more common among people who believe that they aren’t good at STEM? Is discursive distancing less common among people who pursue STEM careers? Is there a correlation between distancing and test scores?

 

Awkwardness in STEM education is fertile ground for qualitative researchers. To what extent is the learning or solving process emphasized and to what extent is the answer valued above all else? How is mathematical language socialized? The process of solving technical problems is a messy and uncomfortable one. It rarely goes smoothly, and in fact challenges often lead to more challenges. The process of trying and failing or trying and learning is not a sexy or attractive one, and there is rampant concern that focusing on the process of learning robs students of the ability to demonstrate their knowledge in a way that matters to people who speak the traditional languages of math and science.

 

We spoke a little about the phenomena of connected math. It sounds to me very closely parallel to project based learning initiatives in physics. I was left wondering why such a similar teaching process could be valued as a teaching tool for all students in one field and relegated to a teaching tool for struggling students in another neighboring field. I wonder about the similarities and differences between the outcomes of these methods. Much of this may rest on politics, and I suspect that the politics are rooted in deeply held and less questioned beliefs about STEM education.

 

STEM education initiatives have grown quite a bit in recent years, and it’s clear that there is quite a bit of interesting research left to be done.

Upcoming DC Event: Online Research Offline Lunch

ETA: Registration for this event is now CLOSED. If you have already signed up, you will receive a confirmation e-mail shortly. Any sign-ups after this date will be stored as a contact list for any future events. Thank you for your interest! We’re excited to gather with such a diverse and interesting group.

—–

Are you in or near the DC area? Come join us!

Although DC is a great meeting place for specific areas of online research, there are few opportunities for interdisciplinary gatherings of professionals and academics. This lunch will provide an informal opportunity for a diverse set of online researchers to listen and talk respectfully about our interests and our work and to see our endeavors from new, valuable perspectives.

Date & Time: August 6, 2013, 12:30 p.m.

Location: Near Gallery Place or Metro Center. Once we have a rough headcount, we’ll choose an appropriate location. (Feel free to suggest a place!)

Please RSVP using this form:

Spam, Personal histories and Language competencies

Over the recent holiday, I spent some time sorting through many boxes of family memorabilia. Some of you have probably done this with your families. It is fascinating, sentimental and mind-boggling. Highlights include both the things that strike a chord and things that can be thrown away. It’s a balance of efficiency and sap.

 

I’m always amazed by the way family memorabilia tells both private, personal histories and larger public ones. The boxes I dealt with last week were my mom’s, and her passion was politics. Even the Christmas cards she saved give pieces of political histories. Old thank you cards provide unknown nuggets of political strategy. She had even saved stirrers and plastic cups from an inauguration!

 

Campaign button found in the family files

Campaign button found in the family files

 

 

My mom continued to work in politics throughout her life, but the work that she did more recently is understandably fresher and more tangible for me. I remember looking through printed Christmas cards from politicians and wondering why she held on to them. In her later years I worried about her tendency to hold on to mail merged political letters. I wondered if her tendency to personalize impersonal documents made her vulnerable to fraud. To me, her belief in these documents made no sense.

 

Flash forward one year to me sorting through boxes of handwritten letters from politicians that mirror the spam she held on to. For many years she received handwritten letters from elected politicians in Washington. At some point, the handwritten letters evolved into typed letters that were hand-corrected and included handwritten sections. These evolved into typed letters on which the only handwriting was the signature. Eventually, even the signatures became printed. But the intention and function of these letters remained the same, even as their typography evolved. She believed in these letters because she had been receiving them for many decades. She believed they were personal because she had seen more of them that were personal than not. The phrases that I believe to be formulaic and spammy were once handwritten, intentional, personal and probably even heartfelt.

 

 

There are a few directions I could go from here:

 

– I better understand why older people complain about the impersonalization of modern society and wax poetic about the old letter writing tradition. I could include a few anecdotes about older family members.

 

– I’m amazed that people would take the time to write long letters using handwriting that may never have been deciphered

 

– I could wax poetic about some of the cool things I found in the storage facility

 

 

But I won’t. Not in this blog. Instead, I’ll talk about competencies.

 

Spam is a manifest of language competencies, although we often dismiss it as a total lack of language competence. In my Linguistics study, we were quickly taught the mantra “difference, not deficiency.” In fact it takes quite a bit of skill to develop spam letters. In survey research, the survey invitation letters that people so often dismiss have been heavily researched and optimized to yield a maximum response rate. In his book The Sociolinguistics of Globalization, Jan Blommaert details the many competencies necessary to create the Nigerian bank scam letters that were so heavily circulated a few years ago. And now I’ve learned that the political letters that I’m so quick to dismiss as thoughtless mail merges are actually part of a deep tradition of political action. Will that be enough for me to hold on to them? No. But I am saving the handwritten stuff. Boxes and boxes of it!

 

 

One day last week, as I drove to the storage facility I heard an interview with Michael Pollan about Food Literacy. Pollan’s point was that the food draughts in some urban areas are not just a function of access (Food draughts are areas where fresh food is difficult to obtain and grocery stores are few and far between, if they’re available at all). Pollan believes that even if there were grocery stores available, the people in these neighborhoods lack the basic cooking skills to prepare the food. He cited a few basic cooking skills which are not basic to me (partly because I’m a vegetarian, and partly because of the cooking traditions I learned from) as a part of his argument.

 

As a linguist, it is very interesting to hear the baggage that people attach to language metaphorically carried over to food (“food illiteracy”). I wonder what value the “difference, not deficiency” mantra holds here. I’m not ready to believe that people in areas subject to food draught are indeed kitchen illiterate. But I wouldn’t hesitate to agree that their food cultures probably differ significantly from Pollan’s. The basic staples and cooking methods probably differ significantly. Pollan could probably make a lot more headway with his cause if, instead of assuming that the people he is trying to help lack any basic cooking skills, he advocated toward a culture change that included access, attainability, and the potential to learn different practical cooking skills. It’s a subtle shift, but an important one.

 

As a proud uncook, I’m a huge fan of any kind of food preparation that is two steps or less, cheap, easy and fresh. Fast food for me involves putting a sweet potato in the microwave and pressing “potato,” grabbing for an apple or carrots and peanut butter, or tossing chickpeas into a dressing. Slow food involves the basic sautéing, roasting, etc. that Pollan advocates. I imagine that the skills he advocates are more practical and enjoyable for him than they are for people like me, whose mealtimes are usually limited and chaotic. What he calls basic is impractical for many of us. And the differences in time and money involved in uncooking and “basics” add up quickly.

 

 

 

So I’ve taken this post in quite a few directions, but it all comes together under one important point. Different language skills are not a lack of language skills altogether. Similarly, different survival skills are not a total lack of survival skills. We all carry unique skillsets that reflect our personal histories with those skills as well as the larger public histories that our personal histories help to compose. We, as people, are part of a larger public. The political spam I see doesn’t meet my expectations of valuable, personal communication, but it is in fact part of a rich political history. The people who Michael Pollan encounters have ways of feeding themselves that differ from Pollan’s expectations, but they are not without important survival skills. Cultural differences are not an indication of an underlying lack of culture.

2013-07-05 11.13.21

 

Representativeness, qual & quant, and Big Data. Lost in translation?

My biggest challenge in coming from a quantitative background to a qualitative research program was representativeness. I came to class firmly rooted in the principle of Representativeness, and my classmates seemed not to have any idea why it mattered so much to me. Time after time I would get caught up in my data selection. I would pose the wider challenge of representativeness to a colleague, and they would ask “representative of what? why?”

 

In the survey research world, the researcher begins with a population of interest and finds a way to collect a representative sample of the population for study. In the qualitative world that accompanies survey research units of analysis are generally people, and people are chosen for their representativeness. Representativeness is often constructed by demographic characteristics. If you’ve read this blog before, you know of my issues with demographics. Too often, demographic variables are used as a knee jerk variable instead of better considered variables that are more relevant to the analysis at hand. (Maybe the census collects gender and not program availability, for example, but just because a variable is available and somewhat correlated doesn’t mean that it is in fact a relevant variable, especially when the focus of study is a population for whom gender is such an integral societal difference.)

 

And yet I spent a whole semester studying 5 minutes of conversation between 4 people. What was that representative of? Nothing but itself. It couldn’t have been exchanged for any other 5 minutes of conversation. It was simply a conversation that this group had and forgot. But over the course of the semester, this piece of conversation taught me countless aspects of conversation research. Every time I delved back into the data, it became richer. It was my first step into the world of microanalysis, where I discovered that just about anything can be a rich dataset if you use it carefully. A snapshot of people at a lecture? Well, how are their bodies oriented? A snapshot of video? A treasure trove of gestures and facial expressions. A piece of graffiti? Semiotic analysis! It goes on. The world of microanalysis is built on the practice of layered noticing. It goes deeper than wide.

 

But what is it representative of? How could a conversation be representative? Would I need to collect more conversations, but restrict the participants? Collect conversations with more participants, but in similar contexts? How much or how many would be enough?

 

In the world of microanalysis, people and objects constantly create and recreate themselves. You consistently create and recreate yourself, but your recreations generally fall into a similar range that makes you different from your neighbors. There are big themes in small moments. But what are the small moments representative of? Themselves. Simply, plainly, nothing more and nothing else. Does that mean that they don’t matter? I would argue that there is no better way to understand the world around us in deep detail than through microanalysis. I would also argue that macroanalysis is an important part of discovering the wider patterns in the world around us.

 

Recently a NY Times blog post by Quentin Hardy has garnered quite a bit of attention.

Why Big Data is Not Truth: http://bits.blogs.nytimes.com/2013/06/01/why-big-data-is-not-truth/

This post has really struck a chord with me, because I have had a hard time understanding Hardy’s complaint. Is big data truth? Is any data truth? All data is what it is; a collection of some sort, collected under a specific set of circumstances. Even data that we hope to be more representative has sampling and contextual limitations. Responsible analysts should always be upfront about what their data represents. Is big data less truthful than other kinds of data? It may be less representative than, say, a systematically collected political poll. But it is what it is: different data, collected under different circumstances in a different way. It shouldn’t be equated with other data that was collected differently. One true weakness of many large scale analyses is the blindness to the nature of the data, but that is a byproduct of the training algorithms that are used for much of the analysis. The algorithms need large training datasets, from anywhere. These sets often are developed through massive web crawlers. Here, context gets dicey. How does a researcher represent the data properly when they have no idea what it is? Hopefully researchers in this context will be wholly aware that, although their data has certain uses, it also has certain [huge] limitations.

 

I suspect that Hardy’s complaint is with the representations of massive datasets collected from webcrawlers as a complete truth from which any analyses could be run and all of the greater truths of the world could be revealed. On this note, Hardy is exactly right. Data simply is what it is, nothing more and nothing less. And any analysis that focuses on an unknown dataset is just that: an analysis without context. Which is not to say that all analyses need to be representative, but rather that all responsible analyses of good quality need to be self aware. If you do not know what the data represents and when and how it was collected, then you cannot begin to discuss the usefulness of any analysis of it.

The curse of the elevator speech

Yesterday I was involved in an innocent watercooler chat in which I was asked what Sociolinguistics is. This should be an easy enough question, because I just got a master’s degree in it. But it’s not. Sociolinguistics is a large field that means different things to different people. For every way of studying language, there are social and behavioral correlates that can also be studied. So a sociolinguist could focus on any number of linguistic areas, including phonology, syntax, semantics, or, in my case, discourse. My studies focus on the ways in which people use language, and the units of analysis in my studies are above the sentence level. Because Linguistics is such a large and siloed field, explaining Sociolinguistics through the lens of discourse analysis feels a bit like explaining vegetarianism through a pescatarian lens. The real vegetarians and the real linguists would balk.

There was a follow up question at the water cooler about y’all. “Is it a Southern thing?” My answer to this was so admittedly lame that I’ve been trying to think of a better one (sometimes even the most casual conversations linger, don’t they?).

My favorite quote of this past semester was from Jan Blommaert: “Language reflects a life, and not just a birth, and it is a life that is lived in a real sociocultural, historical and political space” Y’all has long been considered a southernism, but when I think back to my own experience with it, it was never about southern language or southern identity. One big clue to this is that I do sometimes use y’all, but I don’t use other southern language features along with it.

If I wanted to further investigate y’all from a sociolinguistic perspective, I would take language samples, either from one or a variety of speakers (and this sampling would have clear, meaningful consequences) and track the uses of y’all to see when it was invoked and what function it serves when invoked. My best, uninformed guess is that it does relational work and invokes registers that are more casual and nonthreatening. But without data, that is nothing but an uninformed guess.

This work has likely been done before. It would be interesting to see.
(ETA: Here is an example of this kind of work in action, by Barbara Johnstone)

Revisiting Latino/a identity using Census data

On April 10, I attended a talk by Jennifer Leeman (Research Sociolinguist @Census and Assistant Professor @George Mason) entitled “Spanish and Latino/a identity in the US Census.” This was a great talk. I’ll include the abstract below, but here are some of her main points:

  • Census categories promote and legitimize certain understandings, particularly because the Census, as a tool of the government, has an appearance of neutrality
  • Census must use categories from OMB
  • The distinction between race and ethnicity is fuzzy and full of history.
    • o   In the past, this category has been measured by surname, mothertongue, birthplace
      o   Treated as hereditary (“perpetual foreigner” status)
      o   Self-id new, before interviewer would judge, record
  • In the interview context, macro & micro meet
    • o   Macro level demographic categories
    • o   Micro:
      • Interactional participant roles
      • Indexed through labels & structure
      • Ascribed vs claimed identities
  • The study: 117 telephone interviews in Spanish
    • o   2 questions, ethnicity & race
    • o   Ethnicity includes Hispano, Latino, Español
      • Intended as synonyms but treated as a choice by respondents
      • Different categories than English (Adaptive design at work!)
  • The interviewers played a big role in the elicitation
    • o   Some interviewers emphasized standardization
      • This method functions differently in different conversational contexts
    • o   Some interviewers provided “teaching moments” or on-the-fly definitions
      • Official discourses mediated through interviewer ideologies
      • Definitions vary
  • Race question also problematic
    • o   Different conceptions of Indioamericana
      • Central, South or North American?
  • Role of language
    • o   Assumption of monolinguality problematic, bilingual and multilingual quite common, partial and mixed language resources
    • o   “White” spoken in English different from “white” spoken in Spanish
    • o   Length of time in country, generation in country belies fluid borders
  • Coding process
    • o   Coding responses such as “American, born here”
    • o   ~40% Latino say “other”
    • o   Other category ~ 90% Hispanic (after recoding)
  • So:
    • o   Likely result: one “check all that apply” question
      • People don’t read help texts
    • o   Inherent belief that there is an ideal question out there with “all the right categories”
      • Leeman is not yet ready to believe this
    • o   The takeaway for survey researchers:
      • Carefully consider what you’re asking, how you’re asking it and what information you’re trying to collect
  • See also Pew Hispanic Center report on Latino/a identity

 

 

 ABSTRACT

Censuses play a crucial role in the institutionalization and circulation of specific constructions of national identity, national belonging, and social difference, and they are a key site for the production and institutionalization of racial discourse (Anderson 1991; Kertzer & Arel 2002; Nobles 2000; Urla 1994).  With the recent growth in the Latina/o population, there has been increased interest in the official construction of the “Hispanic/Latino/Spanish origin” category (e.g., Rodriguez 2000; Rumbaut 2006; Haney López 2005).  However, the role of language in ethnoracial classification has been largely overlooked (Leeman 2004). So too, little attention has been paid to the processes by which the official classifications become public understandings of ethnoracial difference, or to the ways in which immigrants are interpellated into new racial subjectivities.

This presentation addresses these gaps by examining the ideological role of Spanish in the history of US Census Bureau’s classifications of Latina/os as well as in the official construction of the current “Hispanic/Latino/Spanish origin” category. Further, in order to gain a better understanding of the role of the census-taking in the production of new subjectivities, I analyze Spanish-language telephone interviews conducted as part of Census 2010.  Insights from recent sociocultural research on the language and identity (Bucholtz and Hall 2005) inform my analysis of how racial identities are instantiated and negotiated, and how respondents alternatively resist and take up the identities ascribed to them.

* Dr. Leeman is a Department of Spanish & Portuguese Graduate (GSAS 2000).

Digital Democracy Remixed

I recently transitioned from my study of the many reasons why the voice of DC taxi drivers is largely absent from online discussions into a study of the powerful voice of the Kenyan people in shaping their political narrative using social media. I discovered a few interesting things about digital democracy and social media research along the way, and the contrast between the groups was particularly useful.

Here are some key points:

  • The methods of sensemaking that journalists use in social media is similar to other methods of social media research, except for a few key factors, the most important of which is that the bar for verification is higher
  • The search for identifiable news sources is important to journalists and stands in contrast with research methods that are built on anonymity. This means that the input that journalists will ultimately use will be on a smaller scale than the automated analyses of large datasets widely used in social media research.
  • The ultimate information sources for journalists will be small, but the phenomena that will capture their attention will likely be big. Although journalists need to dig deep into information, something in the large expanse of social media conversation must capture or flag their initial attention
  • It takes some social media savvy to catch the attention of journalists. This social media savvy outweighs linguistic correctness in the ultimate process of getting noticed. Journalists act as intermediaries between social media participants and a larger public audience, and part of the intermediary process is language correcting.
  • Social media savvy is not just about being online. It is about participating in social media platforms in a publicly accessible way in regards to publicly relevant topics and using the patterned dialogic conventions of the platform on a scale that can ultimately draw attention. Many people and publics go online but do not do this.

The analysis of social media data for this project was particularly interesting. My data source was the comments following this posting on the Al Jazeera English Facebook feed.

fb

It evolved quite organically. After a number of rounds of coding I noticed that I kept drawing diagrams in the margins of some of the comments. I combined the diagrams into this framework:

scales

Once this framework was built, I looked closely at the ways in which participants used this framework. Sometimes participants made distinct discursive moves between these levels. But when I tried to map the participants’ movements on their individual diagrams, I noticed that my depictions of their movements rarely matched when I returned to a diagram. Although my coding of the framework was very reliable, my coding of the movements was not at all. This led me to notice that oftentimes the frames were being used more indexically. Participants were indexing levels of the frame, and this indexical process created powerful frame shifts. So, on the level of Kenyan politics exclusively, Uhuru’s crimes had one meaning. But juxtaposed against the crimes of other national leaders’ Uhuru’s crimes had a dramatically different meaning. Similarly, when the legitimacy of the ICC was questioned, the charges took on a dramatically different meaning. When Uhuru’s crimes were embedded in the postcolonial East vs West dynamic, they shrunk to the degree that the indictments seemed petty and hypocritical. And, ultimately, when religion was invoked the persecution of one man seemed wholly irrelevant and sacrilegious.

These powerful frame shifts enable the Kenyan public to have a powerful, narrative changing voice in social media. And their social media savvy enables them to gain the attention of media sources that amplify their voices and thus redefine their public narrative.

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