Technoscience and Scallops: Actor-Network Theory (ANT)

As a framework and approach to social theory and research, A.N.T. is centered around science and technology, but is by no means limited to it.

actor-network theory ANT

By Melody Xu

Illustration by Charlotte Southall

The traditional view of science and technology holds that what the two different fields hope to achieve are in stark contrast: Galileo “discovered” the phases of Venus, but these phases existed prior to his “discovery.” Diesel “invented” the diesel engine, which did not exist before his invention. However, the foundation of actor-network theory (A.N.T.) stands on the claim of technoscience, which claims that science and technology share the same type of processes rather than having inherently different methods. In this sense, then, what would be perceived as a discovery (science) or an invention (technology) are constructed by the same type of processes. Both can be mapped out by actor-networks. As a framework and approach to social theory and research, A.N.T. is centered around science and technology, but is by no means limited to it.

The actor-network theory, as the name suggests, is composed of actors in networks. Technoscience produces networks, which consists of both human and non-human actors. All actors have their unique set of interests that require accommodation and negotiation in order to be able to work together. What makes A.N.T. so controversial is its insistence on the equal heterogeneity of the actors: there is no methodological difference between human entities and non-human entities. Both types of actors form associations with each other. Their interests not only need to be accommodated to by others, but also used and managed as well. The relationship between actors is then a two-way street of influence and actors are not limited to one network at a time. Everything, from chemicals to elections, contribute to the formation of these intricate networks.

To better understand the intricately complex concept of actor-network, I’ll be utilizing the classic example from Michel Callon, which was introduced in the late twentieth century and has been used to introduce the idea to me in multiple university courses I’ve taken. Let’s set the stage for this example: The location is St. Brieuc Bay in northwestern France, during the 1970s. Scallops were severely over-farmed in order to meet the consumer demand. As a result, the stocks in St. Brieuc Bay were rapidly declining. There had been no prior research done on the early stages of scallop development by scientists at the time, but there was a tentative solution that was found in the Japanese commercial scallop-harvesting techniques of the time. Three scientists at the time were interested in seeing if these tactics were limited to Japan in their successful application or if they could be utilized universally. The question that they were hoping to answer, then, was whether the Japanese techniques could be transferred to St. Brieuc Bay scallops. Eventual results of trying to solve this problem included advancement in the academic knowledge of scallop development, as well as the economic interest of the St. Brieuc Bay fishermen who would profit greatly from the successful transfer.

There are a few steps involved in completing an A.N.T. analysis of a situation: (1) problematization, (2) interessement, (3) enrollment, and (4) mobilization. The first step of setting up any A.N.T. analysis is known as “problematization,” in which we must identify the primary actor to examine the situation through. Any situation or scenario will be different depending on whose eyes you decide to use as a lense to look through, and an actor-network theory analysis of any situation is no different. In this case, the primary actor that we’ll be selecting will be the three researchers who had previously studied the Japanese techniques thoroughly and wish to see if they can be applied elsewhere. Other relevant actors to this conflict, who will be influencing and be influenced by the researchers, would be the fishermen of St. Brieuc Bay, the scientific colleagues of the researchers, and— drumroll please for our first non-human actor— the scallops of St. Brieuc Bay themselves. These actors have their own respective motives: profit, knowledge of scallops, and survival.

The next two steps, called “interessement” and “enrollment”, refer to the process of negotiation and compromise to persuade the actors to identify with their roles, as well as gett the actors to then act out their roles. The number of actors in the world are endless and do not automatically link up to form networks; once a primary actor identifies a problem that they wish to be resolved, they will need to encourage other actors to join their specific network and play their individual parts. For instance, the three researchers attempt to impose and stabilize the identity of the fishermen and the scallops, utilizing the interests of the others to, in essence, make them a part of the researchers’ network. The fishermen of St. Brieuc bay are encouraged to help the scientists through the promise of profits. The scientific colleagues of the researchers will provide academic peer support because the situation will offer more research on a topic they too are interested in. And finally, the scallops are “encouraged” to take part in solving the problem through the protection of the scallop larvae from entities that threaten its survival, such as currents and starfish, by the towlines that will be used to conduct the research. Essentially, these two steps entail the persuasion of all the actors through the alignment of their personal motives with those of the primary actor, thus ensuring a path that is set on solving the problem that is identified in the first step.

The fourth step, “mobilization,” is the process in which actors are justified in representing their constituents.  Are the scallop larvae that the researchers used in their research able to represent the entire scallop population of St. Brieuc Bay? Are the inductive inferences that were made about the scallops representative of the general scallop population? Does the group representatives of the fishermen community that the researchers negotiated with accurately reflect the interests of the group as a whole? These are just some of the questions that must be answered in order to have made an effective actor-network theory analysis of a conflict.

The perceived advantage of actor network theory as a lense of study comes into play when it comes to observing controversies in technoscience. What A.N.T. does is attempt to explain these controversies as the interests of the various actors coming in conflict with one another, therefore relying on the local relationships and dynamics as the answer, as opposed to more global and abstract concepts such as “society” or “social forces.” In traditional sociology, the rule is static order and the exceptions that must be studied are dynamic change. Actor network theory manages to switch it around, with the rule not being static order but the dynamic relatedness of the actors, with long-term stability and order being the focus of study.

While the actor network theory is not without its critics, it is an intriguing lense to look at the world through. As mentioned before, A.N.T. is not limited to the study of technoscientific controversies. Anything and everything around us can be described as being a part of a complex network, from the construction of the New York City subway system to you sitting with your laptop watching The Office on Netflix. For instance, you could look at something like the network of YouTube, with the website being the primary actor at the center and uploaders, subscribers, editing software company, computers, engineers, the board of directors at the YouTube HQ, and advertisers all with different motives being persuaded to play and act out in a specific way. The next time you have a few minutes to spare, try sitting down with a pen and a piece of paper and mapping a network of connections out— the sheer size of the network might just surprise you.

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