This post is part of a series to explore lessons learned from qualitative research articles published in 2017 SAGE journals.
Two ethnographies were popular with readers of SAGE journal articles in 2017. “Knowledge of practice: A multi-sited event ethnography of border security fairs in Europe and North America” was most cited (Baird, 2017) and “Algorithms as culture: Some tactics for the ethnography of algorithmic systems” was most downloaded (Seaver, 2017).
Before looking at these two very different ethnographic studies, what is ethnography? Given defines it as:
Ethnography is the art and science of describing a group or culture. The ethnographer enters the field with an open mind, not with an empty head. Before asking the first question in the field, the ethnographer begins with a problem, a theory or model, a research design, specific data collection techniques, tools for analysis, and a specific writing style. A series of quality controls, such as triangulation, contextualization, and a nonjudgmental orientation, place a check on the negative influence of bias.
The ethnographer is interested in understanding and describing a social and cultural scene from the emic or insider’s perspective. The ethnographer is both storyteller and scientist; the closer the readers of an ethnography come to understanding the native’s point of view, the better the story and the better the science. (Given, 2008, p. 289)
Ethnographic researchers look at groups or cultures, social and cultural scenes, in organizations, societies, and the virtual world. How they define culture varies widely, making this methodology that can be used to study a wide range of research problems. The selected articles illustrate this range: Baird (2017) looked at the cultures of border security, while Seaver (2017) looked at algorithms in culture and as culture.
Some ethnographers spend lengthy periods of time in a setting in order to understand the culture. Baird suggests that ethnographic methods can also be used to study short-term events, in the case of his article, the events were security fairs. His multi-sited event ethnography studied four fairs. He described this as “a composite approach to studying local environments and events that have distinct transnational elements at play. In the context of this study, it involves juxtaposing and relating fieldwork materials from two or more events in order to reflexively understand knowledge of practice of (in)security professionals” (p.189). He draws on the work of Marcus (1995, 1999) to further define multi-sited ethnography as an approach that allows the researcher to follow practices and knowledges across sites. Once he was able to access the security fair events in Europe and North America, he collected data such as “Fieldnotes of observations and experiences, photos, video, audio recordings, conference literature and presentations, advertisements, exhibition items, and other ‘found materials’ form the primary data across the events” (p. 190).
Given pointed to the roles of storyteller and scientist, roles Baird demonstrated in his tales of events that by their nature are close to wide attendance. While this particular article would be of great interest to people in the security field, the ethnographic methods could be applied to other explorations of professional culture is represented by conferences and trade events where people within a field or industry share and develop knowledge.
Seaver’s (2017) study demonstrates the expansion of ethnography to include studies of technology. As a “scavenging ethnographer” Seaver aimed: “to discover what algorithms are, in practice” (p. 2). This article was part of a special issue on Algorithms and Culture for the journal, Big Data, & Society. He chose to use ethnography for this research because:
Ethnographic methods help us gain purchase on topics that concern critical scholars: the interrelation of people and computers, the local production of abstract representations, and the human sensemaking that pervades algorithmic operations, locating these within sociocultural contexts that are diverse and changing. (p. 5)
Data collection included interviews, as well as analysis of advertisements, blog posts. Through this study Seaver was able to discuss algorithms as a part of culture, in contrast to previous studies of algorithms as abstract procedures.
Groups and cultures are everywhere, so the world is an oyster for ethnographic researchers. The only limiting factors for ethnography might be the time and commitment of the researcher.
Your thoughts? Have you conducted ethnographic research? Feel free to use the comment area to share your experiences or add more examples of well-designed ethnographic studies.
Baird, T. (2017). Knowledge of practice: A multi-sited event ethnography of border security fairs in Europe and North America. Security Dialogue, 48(3), 187-205. doi:10.1177/0967010617691656
Given, L. (2008). Ethnography. In L. Given (Ed.), The SAGE Encyclopedia of Qualitative Research Methods. Thousand Oaks, California: SAGE Publications.
Seaver, N. (2017). Algorithms as culture: Some tactics for the ethnography of algorithmic systems. Big Data & Society, 4(2), 2053951717738104. doi:10.1177/2053951717738104