Documentary and Public Film Financing
Documentary filmmaking is a rich field for the application of digital innovation. Both in the use of new tools to tell engaging, interactive, transmedia stories such as through the OpenDocLab, and in the evaluation of the impact of such creative work, for example the application of computational analysis in determining change in people’s knowledge and/ or behavior (Diesner et al. 2014).
I am interested in finding a consistent through-line of understanding that best enables both my research and teaching. A perspective or set of resources to answer Aslinger and Huntemann’s question: “what do we need to learn to be able to participate in conversations about media cultures that are increasingly algorithmic and code-based?” (2013,10).
Digital storytelling tools change both narrative schema and aesthetic presentation in documentaries. Srivasta has described such initiatives as setting a cultural stage for social impact.
Alongside the nature of content - its interactivity, immediacy and continuous nature -which is determined by its digital materiality, also changed are the modes ofcontent diffusion and circulation. Existing channels of transaction and distribution are dissembled and reassembled according to new architectures partially based on new means of content selection (Mangematin et al 2014). For instance: “artists are identified based on the number of views in YouTube or other video channels, users are highly involved in the development of video games and texts are tested on websites before being published” (Mangematin et al 2014). The prevalence of Digital Engagement Metrics e.g. Fandometrics and other data enables creative industries research at unprecedented scale. The availability of big cultural data enables the unprecedented mapping of the industrial geometry of motion pictures at an international scale for example the Kinomatics project (Arrowsmith et al 2014).
A significant proportion of documentary and (European independent fiction) films draw on public finance and/or funding from non-profit institutional actors who seek ROI measured in metrics additional to $revenue.
Funders across the arts are looking to systems of valuation in order that legacy institutions can get up to speed with digital engagement.There are projects in the UK, US, and Australia .Some which put forward normative standards, others enabling users to generate bespoke data collections and many still asking open questions.
There is now a heavyweight set of practical, industry embedded research projects mobilised in the documentary field.
The next step, the gap in industry-academy relations appears to be in linking the results of initiatives with the myriad organisational funders of film.
It is one thing to uncover or determine best practice, it is another to implement it, and importantly – to implement it in an adaptable fashion.
A European documentary may be funded from ten or twenty different sources. Embedding impact measures as part of funding and licensing agreements would be a measure to maximise public spending and also address the opacity that dominates the film industry to the financial detriment of producers (an issue starting to be addressed by Sundance).
Global national film policies are subject to much academic attention, but this is often historical in approach as opposed to practical, needs-led research integrated with action that can be achieved through shared data collection and analysis methods.
Whilst policy connectivity would appear an immediate benefit to impact-related (documentary) film research programmes, this is a complex endeavour. As the QUT team point out in Twitter based research, the territorial construction of meaning in, for example, #tags is incredibly specific, and the relative importance of media channels varies greatly. So potentially we are faced with making a choice between micro-level, project/nation specific guidelines for impact, or an overarching context of cultural principles for impact evaluation for use.
Yet this duality is brings up the false division in theorising individuals and aggregates Latour argues can be dismantled through digital data. I think a quick reference to these arguments in respect of what we are trying to achieve in the doc field, helps to points the direction for where UX and DH methodological development need to progress. This then has implications for teaching.
Political / Theoretical Implications of Digital Data
Traditional explanatory techniques for collective phenomena: an overarching society, neo-classical rational actor models, or emergent structures, all attribute a substantial reality to the aggregate, so individuals are understood to be are ‘in’ a society, or guided by the invisible hand. Latour (2010) argues this is the case because of a historical difficulty in obtaining data. Due to discontinuity in what information is available, and despite starting with individuals, social theorists soon jump to a metaphor of a second, superior level, be it ‘the social’, ‘the economy’ or ‘culture’ as a set of substantive values explaining action (Entwistle and Slater 2013, Callon 1998).
The abilities that digital assemblages offer, to accumulate varying contradictory areas in one space, and to move from individual to aggregate scales without changing lens e.g. within Google Analytics have profound political implications. Digital data enables one to move back and forth seamlessly between individuals with their assembled profiles of attributes, and totalled collectives. Therefore, due to the “coincidence of the conceptual notion of network (action is radically redistributed) and the re-materialisation allowed by digital technology”, the problematic distinction between individual and society is collapsed (Latour 2010, 9).
Digital traces have the benefits of re-materializing, or underlining that which is not usually visible e.g. artists collaborations (Latour 2010). This mapping or bridging function can allow greater understanding of global problems, such as climate change from a human conceptualisation, instead of relying on distancing abstractions such as nature or society as macro concepts (Latour 2011b). For example, research visualising social media responses to natural disasters e.g. at QUT, can achieve a clearer understanding of the world (2014).
However, the navigational tools or datascapes are not yet quite up to the task of mediating between individuals and their aggregates in a smooth enough fashion to make redundant the separation of action and second level structure (Latour 2010). Clicks, nodes and lines need to be developed into a visual means that can both tell complex stories of individuals and their totals.
DH Theory andLearning ways forward / ways forward for learning
Current initiatives are making great strides in this direction. The Kinomatics Project applies a Digital Humanities approach beyond computational replication of humanities methods, to include features of network analysis, and GIS applications in investigating the creative industries including film (Arrowsmith et al 2014).
It is in the creation of such initiatives that theory and praxis are not simply integrated, but demonstrated as mutually constitutive – the linking of practical data for potential policy application as well as toolset provision has pedagogical benefits (Aslinger and Huntemann (2013).
Transmedia documentary is explored as a rigorous and legitimate form of academic research and assessment.
Discussions involving the Mediasmith team concerning creative research methods highlight the importance of such tools in teaching, but reprise Latour’s concern with the digital experience:
“Universities that are locked-into the lecture/seminar/own-study triad… will struggle to adapt to the requirements of a creative-designerly economy. Drawing upon disciplines that already work in these ways is an essential strategy in achieving this turnaround... But! Online digital spaces, when designed really, really well (and I’m not convinced we have anything good enough yet) could do a similar job”
Alongside technical design issues sit the potential problems of established research practices: ”Does a pattern of starting by defining the ‘research question’ hinder the ability for more explorative and creative research methods? Are there other approaches that could be explored that lead to more creative methodologies?” The full exploitation of exploratory processes facilitated by Big Data and Structural Equation Modelling would seem to be hampered by entrenched methodological systems.
So it seems there is a lot of joining-up work to do, between tools and techniques, digital humanities and creative industries, theory and practical political applications
Arrowsmith, C., Verhoeven, D., Davidson, A., & Coate, B. (2014). Kinomatics: A global study into Cinema Data. GSR_3 Geospatial Science Research 3. School of Mathematical and Geospatial Science, RMIT University December 2014
Aslinger, B., & Huntemann, N. B. (2013). Digital media studies futures. Media, Culture & Society, 35(1), 9-12.
Callon, M (ed) 1998, The Laws of the Market. Oxford: Blackwell.
Entwistle, J., & Slater, D. (2013). Reassembling the Cultural: Fashion models, brands and the meaning of ‘culture’after ANT. Journal of Cultural Economy, (ahead-of-print), 1-17
Latour, B. (2010, February). Networks, societies, spheres: Reflections of an actor-network theorist. In International Seminar On Network Theory: Network Multidimensionality In The Digital Age. Annenberg School for Communication and Journalism, Los Angeles, USA.
Latour, B. (2011a). Reflections on Etienne Souriau’s Les différents modes d’existence. The speculative turn: continental materialism and realism, 304-333.
Latour, B. (2011b). Waiting for Gaia. Composing the common world through arts and politics. Lecture, French Institute, London. (nov 2011)
Latour, B. (2013). An inquiry into modes of existence. Harvard University Press.
Latour, B. (2014).Rematerializing Humanities Thanks to Digital Traces. Digital Humanities. Lausanne, Switzerland. 8.7.2014
Mangematin, V., Sapsed, J., & Schüßler, E. (2014). Disassembly and reassembly: An introduction to the Special Issue on digital technology and creative industries. Technological Forecasting and Social Change, 83, 1-9.
Other sources linked.