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Modeling Models: Documentary Filmmaking as a Purposeful Abstraction of the Modeling Process

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Human Simulation: Perspectives, Insights, and Applications

Part of the book series: New Approaches to the Scientific Study of Religion ((NASR,volume 7))

Abstract

This chapter offers a perspective on a how a documentary filmmaker interprets the enterprise of modeling religion for an educated lay public audience. From a methodological standpoint, documenting such a project in film introduces a range of useful questions about the nature of film as data and the nature of film as model. Documentary filmmaking is an interdisciplinary endeavor that demands ethnographic skill, technological acumen and narrative sensitivities—including the ability to balance priorities distinctly different from those of an academic research project.

Inasmuch as a computer model is a purposeful abstraction of reality, an ethnographic documentary film series about the process of building computer models and simulations about religion is itself a purposeful abstraction of this creative process. Taking into account the receptive capacities of an audience more generalized than typical academic journal readers, the filmmaker is required to abstract the practice of modeling in a way that accurately reflects this complicated undertaking in a way that is not too complex for viewers—and that is engaging on a narrative level—but still pursues questions about the procedures and consequences of the Simulating Religion Project. The documentary filmmaker, like the computer simulators themselves, must find a “sweet spot” in model-building that allows for cognitive control of the model, or clarity in image and narrative, while pushing forward a set of specific research questions.

However, the “question” pursued in a documentary miniseries about the Simulating Religion Project is not experimental but rather narrative. This shift in priority—from the investigative to the descriptive—bears greatly on the “data” collected for the “research” embarked upon in documentary film. Data collection with an eye toward narrative also biases the filmmaker to seek universal meanings and concerns throughout the process of filming and interviewing participating researchers. While the Simulating Religion Project might ‘simply’ ask “Can we simulate religion?” Simulating Religion the documentary film seeks a more gripping, universal set of meanings for the project, such as, “Can models of religion predict—and help us stop—religious terrorism?”

The essence of narrative is conflict and tension, but in a research environment the presence of these factors would be not only unprofessional but detrimental to the success of the project. Therefore the filmmaker is tasked with a series of challenges that may not be perfectly in line with the goals of the research project itself. The filmmaker must balance accurate documenting with story construction, and “teach” the process of modeling religion to the audience with a pedagogy that is comprehensible and inviting, yet conveys enough complexity to demonstrate the ambition of the Simulating Religion Project. Despite these challenges, the accessibility and holistic capacity of documentary film to present a “bird’s eye view” of the project over a three-year span in a language that can potentially engage a broad range of viewers make it a valuable tool for communicating complicated research to worlds beyond specialized academic fields.

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Notes

  1. 1.

    CLASP is the Complex Learner Agent Simulation Platform, a platform for developing simulations with a user-friendly interface and requiring no programming expertise.

  2. 2.

    CTM is the Civilizational Transformation Model, an agent-based simulation of civilizational transformation intended to illuminate the social functions of religion in the process of large-scale civilizational change.

  3. 3.

    There is no such thing as raw data. But of all the data forms an anthropologist can collect in order to paint that picture, video evidence—recordings of the subjects in their native habitat—comprises the richest possible data set, bigger than the sum of its parts, diminished when broken into its components. But as rich as it is for recalling interactions and contexts, video is still a fair leap from “reality.” It is still a purposeful abstraction of reality. Raw footage might feel like the closest we can get to an objective record of reality. The video clip still only approximates a fraction of the incredibly rich, encompassing phenomenon of consciousness. Consciousness of reality itself is obstructed by layers of perception and interpretations. Immanuel Kant wrote in 1781 that we can never perceive the world ding an sich—in and of itself—and our experience is always filtered through interpretation. Any collected form of social scientific data, no matter how detailed or vibrant, cannot contain the ding an sich. Like other forms of social scientific data and like consciousness itself, it is hampered by limits imposed by form and perceptive capacities.

  4. 4.

    Such as Joseph Campbell (The Hero With A Thousand Faces, 1970) and Christopher Vogler (The Writer’s Journey: Mythic Structure For Writers, 1998, is a popular screenwriting textbook).

  5. 5.

    The Seven Basic Plots: Why We Tell Stories, Christopher Booker 2004.

  6. 6.

    The three-act structure is cited in Syd Field’s Screenplay (1979), Robert McKee’s Story (2014), and Morton’s A Quick Guide to Screenwriting (2013)—among many others manuals on storytelling, screenwriting and playwriting. This structure is also in dispute and examples of experimental and non-traditionally structured storytelling abound in popular film and fiction works.

  7. 7.

    Which further constrains the data into preconceived parameters.

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Correspondence to Jenn Lindsay .

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Lindsay, J. (2019). Modeling Models: Documentary Filmmaking as a Purposeful Abstraction of the Modeling Process. In: Diallo, S., Wildman, W., Shults, F., Tolk, A. (eds) Human Simulation: Perspectives, Insights, and Applications. New Approaches to the Scientific Study of Religion , vol 7. Springer, Cham. https://doi.org/10.1007/978-3-030-17090-5_7

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