The surprising unpredictability of language in use

This morning I recieved an e-mail from an international professional association that I belong to. The e-mail was in English, but it was not written by an American. As a linguist, I recognized the differences in formality and word use as signs that the person who wrote the e-mail is speaking from a set of experiences with English that differ from my own. Nothing in the e-mail was grammatically incorrect (although as a linguist I am hesitant to judge any linguistic differences as correct or incorrect, especially out of context).

Then later this afternoon I saw a tweet from Twitter on the correct use of Twitter abbreviations (RT, MT, etc.). If the growth of new Twitter users has indeed leveled off then Twitter is lucky, because the more Twitter grows the less they will be able to influence the language use of their base.

Language is a living entity that grows, evolves and takes shape based on individual experiences and individual perceptions of language use. If you think carefully about your experiences with language learning, you will quickly see that single exposures and dictionary definitions teach you little, but repeated viewings across contexts teach you much more about language.

Language use is patterned. Every word combination has a likelihood of appearing together, and that likelihood varies based on a host of contextual factors. Language use is complex. We use words in a variety of ways across a variety of contexts. These facts make language interesting, but they also obscure language use from casual understanding. The complicated nature of language in use interferes with analysts who build assumptions about language into their research strategies without realizing that their assumptions would not stand up to careful observation or study.

I would advise anyone involved in the study of language use (either as a primary or secondary aspect of their analysis) to take language use seriously. Fortunately, linguistics is fun and language is everywhere. So hop to it!

Advertisements

Great description of a census at Kakuma refugee camp

It’s always fun for a professional survey researcher to stumble upon a great pop cultural reference to a survey. Yesterday I heard a great description of a census taken at Kakuma refugee camp in Kenya. The description was in the book I’m currently reading: What Is the What by Dave Eggers (great book, I highly recommend it!). The book itself is fiction, loosely based on a true story, so this account likely stems from a combination of observation and imagination. The account reminds me of some of the field reports and ethnographic findings in other intercultural survey efforts, both national (US census) and inter or multinational.

To set the stage, Achak is the main character and narrator of the story. He is one of the “lost boys” of Sudan, and he found his way to Kakuma after a long and storied escape from his war-ravaged hometown. At Kakuma he was taken in by another Denka man, named Gop, who is acting as a kind of father to Achak.

What is the What by Dave Eggers

What is the What by Dave Eggers

“The announcement of the census was made while Gop was waiting for the coming of his wife and daughters, and this complicated his peace of mind. To serve us, to feed us, the UNHCR and Kakuma’s many aid groups needed to know how many refugees were at the camp. Thus, in 1994 they announced they would count us. It would only take a few days, they said. To the organizers I am sure it seemed a very simple, necessary, and uncontroversial directive. But for the Sudanese elders, it was anything but.

—What do you think they have planned? Gop Chol wondered aloud.

I didn’t know what he meant by this, but soon I understood what had him, and the majority of Sudanese elders, greatly concerned. Some learned elders were reminded of the colonial era, when Africans were made to bear badges of identification on their necks.

—Could this counting be a pretext of a new colonial period? Gop mused.—It’s very possible.
Probable even!

I said nothing.

At the same time, there were practical, less symbolic, reasons to oppose the census, including the fact that many elders imagined that it would decrease, not increase, our rations. If they discovered there were fewer of us than had been assumed, the food donations from the rest of the world would drop. The more pressing and widespread fear among young and old at Kakuma was that the census would be a way for the UN to kill us all. These fears were only exacerbated when the fences were erected.

The UN workers had begun to assemble barriers, six feet tall and arranged like hallways. The fences would ensure that we would walk single file on our way to be counted, and thus counted only once. Even those among us, the younger Sudanese primarily, who were not so worried until then, became gravely concerned when the fences went up. It was a malevolent-looking thing, that maze of fencing, orange and opaque. Soon even the best educated among us bought into the suspicion that this was a plan to eliminate the Dinka. Most of the Sudanese my age had learned of the Holocaust, and were convinced that this was a plan much like that used to eliminate the Jews in Germany and Poland. I was dubious of the growing paranoia, but Gop was a believer. As rational a man as he was, he had a long memory for injustices visited upon the people of Sudan.

—What isn’t possible, boy? he demanded.—See where we are? You tell me what isn’t possible at this time in Africa!

But I had no reason to distrust the UN. They had been feeding us at Kakuma for years. There was not enough food, but they were the ones providing for everyone, and thus it seemed nonsensical that they would kill us after all this time.

—Yes, he reasoned,—but see, perhaps now the food has run out. The food is gone, there’s no more money, and Khartoum has paid the UN to kill us. So the UN gets two things: they get to save food, and they are paid to get rid of us.

—But how will they get away with it?

—That’s easy, Achak. They say that we caught a disease only the Dinka can get. There are always illnesses unique to certain people, and this is what will happen. They’ll say there was a Dinka plague, and that all the Sudanese are dead. This is how they’ll justify killing every last one of us.
—That’s impossible, I said.

—Is it? he asked.—Was Rwanda impossible?

I still thought that Gop’s theory was unreliable, but I also knew that I should not forget that there were a great number of people who would be happy if the Dinka were dead. So for a few days, I did not make up my mind about the head count. Meanwhile, public sentiment was solidifying against our participation, especially when it was revealed that the fingers of all those counted, after being counted, would be dipped in ink.

—Why the ink? Gop asked. I didn’t know.

—The ink is a fail-safe measure to ensure the Sudanese will be exterminated.

I said nothing, and he elaborated. Surely if the UN did not kill us Dinka while in the lines, he theorized, they would kill us with this ink on the fingers. How could the ink be removed? It would, he thought, enter our bodies when we ate.

—This seems very much like what they did to the Jews, Gop said.

People spoke a lot about the Jews in those days, which was odd, considering that a short time before, most of the boys I knew thought the Jews were an extinct race. Before we learned about the Holocaust in school, in church we had been taught rather crudely that the Jews had aided in the killing of Jesus Christ. In those teachings, it was never intimated that the Jews were a people still inhabiting the earth. We thought of them as mythological creatures who did not exist outside the stories of the Bible. The night before the census, the entire series of fences, almost a mile long, was torn down. No one took responsibility, but many were quietly satisfied.

In the end, after countless meetings with the Kenyan leadership at the camp, the Sudanese elders were convinced that the head count was legitimate and was needed to provide better services to the refugees. The fences were rebuilt, and the census was conducted a few weeks later. But in a way, those who feared the census were correct, in that nothing very good came from it. After the count, there was less food, fewer services, even the departure of a few smaller programs. When they were done counting, the population of Kakuma had decreased by eight thousand people in one day.

How had the UNHCR miscounted our numbers before the census? The answer is called recycling.

Recycling was popular at Kakuma and is favored at most refugee camps, and any refugee anywhere in the world is familiar with the concept, even if they have a different name for it. The essence of the idea is that one can leave the camp and re-enter as a different person, thus keeping his first ration card and getting another when he enters again under a new name. This means that the recycler can eat twice as much as he did before, or, if he chooses to trade the extra rations, he can buy or otherwise obtain anything else he needs and is not being given by the UN—sugar, meat, vegetables. The trading resulting from extra ration cards provided the basis for a vast secondary economy at Kakuma, and kept thousands of refugees from anemia and related illnesses. At any given time, the administrators of Kakuma thought they were feeding eight thousand more people than they actually were. No one felt guilty about this small numerical deception.

The ration-card economy made commerce possible, and the ability of different groups to manipulate and thrive within the system led soon enough to a sort of social hierarchy at Kakuma.”

An Analytical person at the Nutcracker (or Research Methodology, Nutcracker Style)

Last night we attended a Russian Ballet performance of the Nutcracker. It was a great performance, and fun was had by all.

2013-12-17 18.38.03

Early in the performance I realized that although I have developed some understanding of the ballet, I hadn’t shared any of that knowledge with my kids. At this point, I started whispering to them quietly to explain what they were seeing. I whispered quick, helpful comments, such as “those are toys dancing” and “the kids have gone to sleep now, so this is just the adults dancing.” It wasn’t long into the performance that this dynamic began to change. I realized that their insights were much funnier than mine “wow, that guy should go on ‘So You Think You Can Dance!’ or ‘The Voice’ or something! “and that my comments were starting to be pretty off-base. My comments evolved into a mash-up of “The kids have gone to sleep now” “No, I guess the kids haven’t gone to sleep yet” “I really can’t tell if the kids are still up or not!” and “Those are the sugarplum fairies” “Wait, no, maybe these are the sugar plum fairies?” and “I don’t know, sweetie, just watch them dance!” By the end of the show I had no idea what was going on or why the Chuck.E.Cheese king was dancing around on stage (although one of the girls suspected this particular king was actually a bear?). The mom next to me told me she didn’t know what was going on either “and,” she added, “I go to the Nutcracker every year! Maybe that was what made it a Russian Nutcracker?” …And here I thought the Russian influences were the Matryoshka dolls and the Chinese dancers clothed in yellow (despite the awkward English conversation that the costumes prompted).

At the beginning of the show I was nervous to whisper with my kids, but I soon realized that there was a low hum all around me and throughout the concert hall of people whispering with their kids. This, I think, is what remix research methods should be all about- recording and interviewing many audience members to gain a picture of the many perspectives in their interpretations of the show. Here is a challenge question to my readers who are hipper to qualitative research methods: what research strategy could best capture many different interpretations of the same event?

Earlier this week I spoke with a qualitative researcher about the value of an outsider perspective when approaching a qualitative research project. Here is a good example of this dynamic at play: people clapped at various parts of the performance. I recognized that people were clapping at the end of solo or duo performances (like jazz). If I were to describe these dances, I would use the claps as a natural demarcation, but I probably would not think to make any note of the clapping itself. However, the kids in my crew hadn’t encountered clapping during a show before and assumed that clapping marked “something awesome or special.” Being preteens, the kids wanted to prove that they could clap before everyone else, and then revel in the wave of clapping that they seemingly started. At one point this went awry, and the preteens were the only audience members clapping. This awkward moment may have annoyed some of the people around us, but it really made the little sister’s day! From a research perspective, these kids would be more likely to thoroughly document and describe the clapping than I would, which would make for a much more thorough report. Similarly, from a kids-going-to-a-show perspective this was the first story they told to their Dad when they got home- and one that kicked off the rest of our report with uncontrollable laughter and tears.

As the show went on and appeared not to follow any of the recognizable plot points that I had expected (I expected a progressive journey through worlds experienced from the vantage of a sleigh but instead saw all of the worlds dancing together with some unrecognizable kids variously appearing on a sleigh and the main characters sometimes dancing in the mix or on their own), I began to search for other ways to make sense of the spectacle. I thought of a gymnast friend of mine and our dramatically different interpretations of gymnastics events (me: “Wow! Look what she did!” her: “Eh, she scratched the landing. There will be points off for that.” Which parts of the dancing should I be focusing on? I told my little one “Pay attention, so we can try these moves at home.” Barring any understanding of the technical competencies involved (but sure that laying your body at some of these amazing angles, or somehow spinning on one foot, or lifting another person into the air require tons of training, skills and knowledge) or any understanding of the plot as it was unfolding in front of me, I was left simply to marvel at it all. This is why research is an iterative process. In research, we may begin by marveling, but then we observe, note, and observe again. And who knows what amazing insights we will have developed once the process has run its course enough times for events to start making sense!

To be a researcher is not to understand, but rather to have the potential to understand- if you do the research.

Great readings that might shake you to your academic core? I’m compiling a list

In the spirit of research readings that might shake you to your academic core, I’m compiling a list. Please reply to this thread with any suggestions you have to add. They can be anything from short blog posts (microblog?) to research articles to books. What’s on your ‘must read’ list?

Here are a couple of mine to kick us off:

 

Charles Goodwin’s Professional Vision paper

I don’t think I’ve referred to any paper as much as this one. It’s about the way our professional training shapes the way we see the things around us. Shortly after reading this paper I was in the gym thinking about commonalities between the weight stacks and survey scales. I expect myself to be a certain relative strength, and when that doesn’t correlate with the place where I need to place my pin I’m a little thrown off.

It also has a deep analysis of the Rodney King verdict.

 

Revitalizing Chinatown Into a Heterotopia by Jia Lou

This article is based on a geosemiotic analysis of DC’s Chinatown. It is one of the articles that helped me to see that data really can come in all forms

 

After method: Mess in Social Science Research by John Law

This is the book that inspired this list. It also inspired this blog post.

 

On Postapocalyptic Research Methods and Failures, Honesty and Progress in Research

I’m reading a book that I like to call “post-apocalyptic research methodology.” It’s ‘After Method: Mess in Social Science Research’ by John Law. At this point the book reads like a novel. I can’t quite imagine where he’ll take his premise, but I’m searching for clues and turning pages. In the meantime, I’ve been thinking quite a bit about failure, honesty, uncertainty and humility in research.

How is the current research environment like a utopian society?

The research process is often idealized in public spaces. Whether the goal of the researcher is to publish a paper based on their research, present to an audience of colleagues or stakeholders about their research, or market the product of their research, all researchers have a vested interest in the smoothness of the research process. We expect to approach a topic, perform a series of time-tested methods or develop innovative new methods with strong historical traditions, apply these methods as neatly as possible, and end up with a series of strong themes that describe the majority of our data. However, in Law’s words “Parts of the world are caught in our ethnographies, our histories and our statistics. But other parts are not, and if they are then this is because they have been distorted into clarity.” (p. 2) We think of methods as a neutral middle step and not a political process, and this way of thinking allows us to focus on reliability and validity as surface measures and not inherent questions. “Method, as we usually imagine it, is a system for offering more or less bankable guarantees.” (p. 9)

Law points out that research methods are, in practice, very limited in the social sciences “talk of method still tends to summon up a relatively limited repertoire of responses.” (p. 3) Law also points out that every research method is inherently political. Every research method involves a way of seeing or a way of looking at the data, and that perspective maps onto the findings it yields. Different perspectives yield different findings, whether they are subtly or dramatically different. Law’s central assertion is that methods don’t just describe social realities but also help to create them. Recognizing the footprint of our own methods is a step toward better understanding our data and results.

In practice, the results that we focus on are largely true. They describe a large portion of the data, ascribing the rest of the data to noise or natural variation. When more of our data is described in our results, we feel more confident about our data and our analysis.

Law argues that this smoothed version of reality is far enough from the natural world that it should perk our ears. Research works to create a world that is simple and falls into place neatly and resembles nothing we know, “’research methods’ passed down to us after a century of social science tend to work on the assumption that the world is properly to be understood as a set of fairly specific, determinate, and more or less identifiable processes.” (p. 5) He suggests instead that we should recognize the parts that don’t fit, the areas of uncertainty or chaos, and the areas where our methods fail. “While standard methods are often extremely good at what they do, they are badly adapted to the study of the ephemeral, the indefinite and the irregular.” (p. 4). “Regularities and standardizations are incredibly powerful tools, but they set limits.” (p. 6)

Is the Utopia starting to fall apart?

The current research environment is a bit different from that of the past. More people are able to publish research at any stage without peer review using media like blogs. Researchers are able to discuss their research while it is in progress using social media like Twitter. There is more room to fail publicly than there ever has been before, and this allows for public acknowledgment of some of the difficulties and challenges that researcher’s face.

Building from ashes

Law briefly introduces his vision on p. 11 “My hope is that we can learn to live in a way that is less dependent on the automatic. To live more in and through slow method, or vulnerable method, or quiet method. Multiple method. Modest method. Uncertain method. Diverse method.”

Many modern discussions of about management talk about the value of failure as an innovative tool. Some of the newer quality control measures in aviation and medicine hinge on the recognition of failure and the retooling necessary to prevent or limit the recurrences of specific types of events. The theory behind these measures is that failure is normal and natural, and we could never predict the many ways in which failure could happen. So, instead of exclusively trying to predict or prohibit failure, failures should be embraced as opportunities to learn.

Here we can ask: what can researchers learn from the failures of the methods?

The first lesson to accompany any failure is humility. Recognizing our mistakes entails recognizing areas where we fell short, where our efforts were not enough. Acknowledging that our research training cannot be universal, that applying research methods isn’t always straightforward and simple, and that we cannot be everything to everyone could be an important stage of professional development.

How could research methodology develop differently if it were to embrace the uncertain, the chaotic and the places where we fall short?

Another question: What opportunities to researchers have to be publicly humble? How can those spaces become places to learn and to innovate?

Note: This blog post is dedicated to Dr Jeffrey Keefer @ NYU, who introduced me to this very cool book and has done some great work to bring researchers together

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.

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).