Continuous Skills or Discrete Worlds?
Chambliss' ethnographic study of competitive swimming
I first came across Chambliss’ (1989) ethnographic study of the levels in competitive swimming in a writing course in graduate school. Stylistically, the article veers from the traditional drab and jargon-heavy prose of many an academic article. A mere sixteen pages (short for sociology!), the article is true to its method and filled with quotes from the study participants. It even has a newsworthy topic – Olympic swimming!
I have chosen Chambliss’ article for the launch of Rolling Downhill because these are the qualities I am striving for on the blog. Chambliss isn’t trying to make more of his observations than is warranted; he isn’t spinning a yarn. Yet, it is that clarity that is decisive in my view.
In some circles, Chambliss (1989) is considered a classic and even after 30 years remains on some syllabi, but probably not outside of sociology. I will be making this move regularly at Rolling Downhill: pulling up old research and describing its insight for a research agenda on economic mobility and the future of work.
Careers in Swimming
Chambliss’ research question is timeless: what differentiates excellent performers? The case Chambliss investigates is competitive swimming, but he clearly intends his analysis to be generalizable to a wide range of jobs. It is the research design that makes this study relevant today. First, Chambliss is taking a longitudinal view and studying swimmers’ careers. It is very difficult to speak of mobility without a longitudinal perspective. In studies from this era, longitudinal data on worker’s careers was not readily available (as it still is in many cases today). However, that didn’t stop researchers from taking a longitudinal perspective. The time investment was high: Chambliss reports spending 20 months in participant observation embedded with a swimming team on top of his multiple years of familiarity with the sport and 120 interviews with national and world-class swimmers and coaches.
Second, Chambliss is studying the multiple levels of competitive swimming as it existed in the 1980s United States and watching swimmers’ careers develop. Chambliss describes five levels from low to high: country club teams, city and regional teams, Junior Nationals (under 18), Senior Nationals (all ages), and the Olympic level. Importantly, studying multiple levels allows Chambliss to avoid the pitfall of studying only those who excel, like winners at any level. In research methods parlance, this pitfall is called selecting on the dependent variable and it significantly narrows the scope of the study. For example, if Chambliss only studied those swimmers on the Olympic Team, the research question would be narrowed to: what differentiates excellence among those at the highest level of competition? This is an important question for coaches at the highest level or people seeking to predict the next Gold medalist. Chambliss seeks an answer to the broader question, what differentiates excellence from the bottom to the top of competitive swimming?
Multiple, Discrete Worlds of Competition
The dominant viewpoint on jobs in economics is that they are made of skills and tasks. Jobs exist at particular firms or employers. Skills are a framework for identifying similar jobs across employers and industries. From this perspective, occupations are a group of similar jobs with similar skill and task profiles. Depending on the desired degree of granularity, an occupation category can be broad (e.g. clerical workers, construction trade workers), or more specific (e.g. web developers and telemarketers) with a corresponding degree of skill specificity.
Working from this perspective, competitive swimmers at all levels would conceivably have the same skill and task profile. Indeed, in the 2020 Census Occupational classification system all athletes and sports competitors are linked together under code 2721. O*NET is a database that provides task and skill information for detailed occupations. Under code 27-2021 Athletes and Sport Competitors (yes, the U.S. government has multiple occupational classification systems; no, you don’t want to ask about why), we find for example that these workers need to know how to use email and YouTube and use skills like active listening and critical thinking.
There is no paper ceiling of a college degree for athletes. A high school diploma is the required level of education according to the O*NET profile. Although, perhaps a note of caution since the most decorated U.S. female Olympian swimmer, Katie Ledecky, who won her first Gold medal at age 15 (education: less than a high school diploma), did go on to graduate from Stanford University.
Chambliss enters this conversation by challenging the premise. He argues that competitive swimming isn’t a cohesive category with a similar skill and task profile. There are discrete worlds of swimming with different goals and skills. In practical terms, this means moving to a more competitive level of swimming requires new techniques, habits, and routines – even unlearning old practices. Yes, swimmers are in a pool and they train, but how swimmers go about those activities are so different at each level as to be fundamentally different. Each world in Chambliss’ telling are also different social worlds. The interactions of swimmers, parents, and coaches and the level of organization varies from casual to professional across the levels of the sport.
In the world of sports, I think Chambliss’ conclusions are accepted today. The NFL draft is occurring as I write this. The commenters are all seeking to project how college players will perform in the NFL. Nowadays, there is substantial historical analytics of the performance of players in college and in the NFL. It appears well understood, if not taken-for-granted, that many good college players who are high draft picks will not succeed in the NFL and it isn’t because they lack physical attributes or hard work. The large amount of time and effort teams spend scouting players in an indicator of the difficulty in identifying players who will succeed in the NFL. In Chambliss’ terminology, college football and the NFL are different worlds and this makes past performance only a loose indicator of future excellence.
Discrete Worlds and the Labor Market
Occupations are a tool to group jobs in the labor market and make analyses with limited data tractable. The current classification systems are a 1970s tool that has been updated about once a decade. If you haven’t deduced, the occupational classification systems were built primarily by economists working from a skill paradigm. It is easy to reify the occupational classification system as the labor market and to take occupational categories at meaningful skill or social units. One reason I like to read research from several decades ago is that many researchers were more aware (or more open) about the limitations of their data (and their data was much more limited!) in operationalizing their conceptualization of what they thought was happening.
Sociologists have been more regular users of occupational data in describing labor market dynamics than economists. Yet, our conceptualization of occupations is much more complex than economists (more on this is later posts). The starting point is Chambliss’ discrete worlds perspective. The key is to identify the salient social worlds that demarcate the labor market and then to identify the entry points and pathways into these different worlds. We can’t assume that the entry point to a higher-paid world of the occupation is by working in the job longer and gaining experience. This may be the case for some jobs and occupations, but it is not a given.
A critic might say I took an easy example with swimmers and athletes. Those are a special case – they don’t even count as workers in the traditional sense! A focus of my work has been on low-wage workers, so let’s take another example from that space: waiters and waitresses. There are many types of restaurants. They serve different clientele, have different vibes, and the function of the wait staff is different. Like athletes, there is also an age regime at work with a preference for younger workers. It seems clear to me that the way you get a job as a waiter or waitress and a high-end restaurant with greater tips is not by working at a low-end restaurant for many years. This is not to say that previous experience in the job isn’t relevant, it is simply that the worlds are different enough that other experiences, like the ability to relate to the clientele, may be more relevant.
Yes, but waiters and waitresses are a job with low formal barriers to entry like educational credentials or licensure. Let’s take another example from the credentialed end of the labor market: lawyers. If you follow the news on the law profession, then you may know that the median wages have been stagnating and the profession is moving towards a winner-take-all market. This means there is bigger cliff in terms of wages and career trajectories between those who secure positions at major law firms and companies and those who do not then in the past. There is differentiation between law firms in the type of law and the type of clients and these kinds of product market differences map onto differences in the segmentation of careers in law. Chambliss’ discrete worlds perspective fits well in this context as well.
Chambliss ethnographic and insider-informant research design is an exemplar of the kind of research we need more of if we want to understand how economic mobility is occurring. The proliferation of new data sources on jobs with large sample sizes from administrative data or resumes provide an opportunity to operationalize the discrete social worlds of jobs in ways previously unavailable to quantitative researchers. I envision mixed methods studies to identify the salient social worlds, entry points, and job ladders to specific jobs using the newly available quantitative data and insider-informants. If we want to democratize information on the pathways to jobs, then we need to start by putting in the effort to understand how these labor markets work and how occupational categories are segmented into discrete social worlds.