Labor of Love: Amateurs and Lay-expertise Legitimation in the Early U.S. Radio Field

Abstract

Many actors claim to be experts of specialized knowledge, but for this expertise to be perceived as legitimate, other actors in the field must recognize them as authorities. Using an automated topic-model analysis of historical texts associated with the U.S. amateur radio operator movement between 1899 and 1927, we propose a process model for lay-expertise legitimation as an alternative to professionalization. While the professionalization account depends on specialized work, credentialing, and restrictive jurisdictional control by powerful field actors, our model emphasizes four mechanisms leading to lay-expert recognition: building an advanced collective competence, operating in an unrestricted public space, providing transformational social contributions, and expanding an original collective role identity. Our analysis shows how field expertise can be achieved outside of professional spaces by nonprofessionalized actors who master activities as a labor of love. Our work also reveals that lay-expertise recognition depends on the interplay between collective identities and collective competence among non-professional actors, and it addresses the shifting power dynamics when professional and non-professional actors coexist and strive for expertise recognition.

Theorizing Supply Chains with Qualitative Big Data and Topic Modeling

“…These authors pursued this interest by analyzing the evolution of the U.S. wireless‐radio‐broadcasting industry, in which radio operators, or “hams” as they were called, went from being viewed as a nuisance to their knowledge being viewed over time as important to the profession and collaborating with professionals in the field, including top scientists and Nobel Prize winners. Croidieu and Kim (2018) used topic modeling, but unlike Almquist and Bagozzi (2019), focused on the temporal, evolutionary dynamics of the U.S. radio broadcasting industry.…”

“…Such textual material was assumed to reflect the evolving perceptions of key actors in the early development of U.S. radio broadcasting. Unlike the previously described study, Croidieu and Kim (2018) analyzed the text over time to detect trends in the identified topics in relation to the evolving institutional context of the U.S. radio broadcasting industry at the beginning of the nineteenth century. They aimed to detect topical trends in order to describe the underlying mechanisms that led to the legitimizing of amateur radio operators as industry experts.…”

“…Theorizing from qualitative Big Data can help to render new categories of sustainable practices (Székely & vom Brocke, 2017) but also develop new theory on the temporal dynamics of sustainable practice emergence and legitimization. For example, taking inspiration from the work of Croidieu and Kim (2018), supply chain researchers could scrape data for all the major stakeholder groups active in electronics or apparel industries in the past 15‐20 years, from global manufacturers and their key suppliers to international nongovernmental organizations and activist groups. These corpora of textual data would allow to ask why and how specific sustainable sourcing practices come to dominate the industry and be endorsed by powerful industry associations such as the Responsible Business Alliance or the International Apparel Federation, whereas others are quickly abandoned.…”

“…Kauffman et al (2018) describe the conditions under which buyers and suppliers can “tinker” their interorganizational connections, so they are more adaptive to unanticipated events in the environment, but these authors do not offer insights into the temporal processes by which this happens. The analysis that we propose, which is inspired by the works of Almquist and Bagozzi (2019) and Croidieu and Kim (2018), could reveal the specific mechanisms that make complex supply chain systems more (or less) adaptive.…”

“…This section is followed by illustrations of the application of topic modeling in two different studies in organizational theory journals, with a description of how their analysis can be extended to theorizing supply chains. Specifically, the methods used by Almquist and Bagozzi (2019) can examine the functioning of supply chains, and the methods used by Croidieu and Kim (2018) can examine the temporal dynamics of supply chain emergence and adaptation. We conclude the paper by outlining few cautionary notes for theorizing supply chains from qualitative Big Data.…”