On Narrativization
An Introduction to Narrative-Based Research and a Proposal for New Tools
Andrew Freiband
Faculty (Sabbatical) | Principal Investigator
Dept of Film Animation Video
Rhode Island School of Design
rough draft 07052016
WHAT FILMMAKERS MAY KNOW THAT BEHAVIORAL ECONOMISTS DON'T
Behavioral economics is dedicated to making sense of human-centered systems by understanding irrational human behavior. The aim might be to achieve predictive power over human systems, or to understand large-scale economic phenomena that defies 'Big Data' or quantitative analysis - either for gaining advantage in the market or more benignly for addressing a social order problem or development crisis.
Behavioral economics derives approaches from a number of disciplines, including evolutionary psychology, anthropology, mathematics, and neuroscience. It is a contemporary manifestation of the ageless search for what makes humans act the way they do - only now the search has access to far more powerful methodological and mechanical tools, such as data analysis and high-speed computers.
With all of the technical and informational capacity at the fingertips of the economists, it is possible to see connections between almost all aspects of a system. Many of these connections yield important insights into behavioral motivation in an individual or a society. Yet many more of them are the result of what media theorist Douglas Rushkoff calls 'fractalnoia': the seeing of connective, causative patterns across diverse systems where in fact there is nothing there but self-similarity. Many interventions designed by behavioral economists find themselves missing the point because they're premised on a data-driven perceived connection that is nothing but coincidence or correlation. What is missing is a reliable ability to determine causation. And determining causation where human action is concerned is certainly a qualitative and potentially a highly subjective act.
I think filmmakers - and artists, by extension - do it as a matter of course. Contemporary art practice is very much like a kind of behavioral economics - it is connective, contextual, social, irrational, iterative, and process-oriented (as opposed to being focused on the production of an object). Systems theory is as widely studied by artists today (if not more so) than color theory. This process-orientation in particular can be alienating to anyone outside of the so-called art world who looks at contemporary art through the lens of only what they see in galleries or online - who is looking only at the 'products' contemporary art leaves behind. And that's because, on the one hand, the art market and those who drive it need to keep saleable products in circulation; and on the other because artists (possibly sometimes seduced by that market) do a poor job of visualizing, illustrating, or otherwise communicating the nature of those processes they're engaged in.
This isn't exclusively a knock on artists' writing or promotional skills - rather it's because artists' tools for communicating their processes are obsolete, and these tools aren't good at explicating these processes or their purposes. A part of the ongoing research described in this paper is devoted to conceiving and designing new tools for artists to engage in these complex systems studies - as researchers and not solely as 'visual communicators.' My work is determined to position artists where they are creators of knowledge first and foremost.
Partially because it's my own area of concentration, I will use filmmaking as an example - but I also feel that it serves as a powerful example of how artists' practice can be very easily reframed as being research into causality, and the modification of artists' tools can help us use that research in new ways.
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ON NARRATIVIZATION
Throughout the course of this project, I will refer back to the concept of narrativization, and so it is worthwhile to attempt a definition and a description of how this concept is made manifest through the practice of filmmaking.
We might best summarize narrativization as a kind of articulation - the articulation of a matrix of aspects in a scene, an image, or a situation - which permits the observer to understand that scene, image, or situation in narrative terms. Of course nobody loves a definition that falls back on its own root word, so let's look at what narrative may mean in this context.
Narrative
While there is a huge body of scholarship on the nature of narrative, from my own experience as a filmmaker and teacher I would like to propose that here we define narrative as the perception of causality between disparate elements in a sequence. That sequence could be a sequence of images, or a sequence of experiences, or even a sequence of numbers - human beings experience the world in temporal sequence, and from moment to moment we convince ourselves that one thing must have led to another - we perceive causality. And we make sense of the universe this way, by threading together a narrative in our mind, that explains why we're seeing what we're seeing, when we're seeing it. Adrian Miles writes, in his essay What is it for if not Story, "as a pattern making species we are highly adept at finding and attributing cause between otherwise disparate things, sort of the Kuleshov effect meeting cognitive narrative schemata, combined with our species' assumption that everything is about us."
Social scientists use the term 'sequentiality' to describe their evaluation of the possible sequential relationship between segments, particularly when they're discussing the analysis of ethnographic video. But where social science is obliged to make a notation of possible sequentiality and then move on, the filmmaker must use this concept to actively construct a story - and as a result to determine how adequate the segment's sequentiality may be. Furthermore, the filmmaker is working across a number of different situational matrices, and each of these has its own sequentiality and therefore can possible be narrativized differently; there is the act of being a filmmaker in a given context, there is the selection of context, there is the relating to subsequent audiences, and of course there is the subject context itself - the thing we've chosen to film and study. All of these contexts require a slightly different set of narrativizations, and the overlapping articulation of these perceived causalities can inform what is finally learned from the system. This also brings up the question, what is the resultant product of the act of narrativization? And what can be done with it?
Narrative Literacy
Narrative as a construct of knowledge, with a reliance on sequential information, is eligible for its own kind of literacy. I find myself instructing my students in this literacy as a primary part of being a teacher: we learn how to read images - semiotically, emotionally, rationally, metaphorically, literally - and gain meaning from them. Then we set those images in motion and read the change in meaning. And then we sequence those moving images, and read again how possible meaning is expanded and unfolded almost infinitely, how in the space of a cut, for example, a billion uniquely human neurological processes are invoked and we instantly rationalize the change in image as a change in space, time, subject, interest, and ultimately meaning. All of this is reading - reading images, reading sequences, drawing meaning out of the content and ordering of discrete pieces of information. To promote a complete literacy, however, reading is not enough. I must also guide students in developing the ability to write - to make meaningful images, set them in motion without losing control of their reception in the minds of viewers, and create sequences that lead where they intend (even if that intention is ultimately chaotic, and that controlled steering is deliberately off a metaphorical or psychic cliff).
There's a vast matrix of semiotic information in any section of moving image - some of this information is universally human (the sun represents daytime), and much of it is culturally specific (is it also God, or a bringer of life, or death, the center of the universe, or merely a medium-sized star - what emotions, memories, associations accompany its image?) Another challenge for the mediamaker - each audience's cultural makeup will shape their perception of causality and meaning in the moving images. A viewer rapidly processes all of this information according to their own acquired set of fluencies, and just as rapidly assembles perceptions and idea from this image stream. And because of the centrality of pattern-making and reliance on perceived cause-and-effect, we work to cobble together narrative from these sequences.
Narrative, then, is an understanding of causality between sequentially-arranged experiences; writers, filmmakers, and other storytellers exploit this perception and build larger structures out of the smaller unit of 'narrative', and these are stories. Beginnings, middles, and ends - whatever structure we feel is required of a story, is in some way built from a number of smaller instances of perceived causality.
We must not only be literate in the images and temporality of the media we're making, but we must also know how to write in the minds of our audiences, be they a single individual or a mass population. Narrative is more than a perception, it is a discourse between producer and viewer. The only way to teach narrative literacy, then, is to make work, watch work, talk about work, and remake work. A constant cycle, the work itself never finished but dynamic, alive, changeable as time passes and audiences and circumstances change. This may be different than a more product-focused and academic way of learning to make a certain kind of movie. But this dynamic process-based mode of mediamaking has been what's allowed me to see the informational value in narrative data, and to suggest to me that it be usable for rigorous learning, and not just re-presentation of the world as it already exists into pleasing or entertaining or enlightening forms.
Practical Applications
Before describing the methodology and introducing the concept for the toolsets, first let us consider the nascence of this study and look at some examples of how this research could be applied.
With a background in fine arts media, nonfiction film and television production, and extensive experience as a media educator, I was working as a commissioned video producer for USAID (U.S. Agency for International Development) to document selected project implementations overseas. With a very small crew, we would travel to Africa, South America, and Latin America to film and tell the story of USAID-supported projects there, with an emphasis on USAID's support of innovation and entrepeneurship. These were new models of international development, often relying on new technologies or innovative models of partnership with project implementers - in other words, even though it was development work, the projects themselves sometimes took forms that were unusual and therefore difficult for USAID's own officers to get the full picture of. Some of these included technology-based partnerships with an American agricultural university and a Haitian steep-hillside farming cooperative, utilizing new methods of greenhousing and terracing to address Haiti's agricultural sustainability as well as its catastrophic mountain deforestation; or support of entrepeneurs in East Africa developing new economic models and recycling technologies to address the absence of sanitation in the vast slums of major African cities...
With sometimes minimal briefing, or even inaccurate briefing, from project officers in Washington, DC, we would land and gain firsthand introduction to the project and then employ familiar nonfiction filmmaking methodologies (interviews, process shooting, b-roll for illustration) to build a story for the purpose of publishing a short essentially 'promotional' video. USAID needs to regularly publish such media pieces to emphasize the scope and effect of its work to garner continued public (and Congressional) support, as well as to compellingly and efficiently elucidate these projects during presentations and discussions.
Because I was there as a filmmaker and was charged with 'telling a story' about whatever it was we were there to illustrate, I was essentially free to pursue pathways through the project that I felt would most likely yield a compelling - but also accurate - story. USAID, or embassy staff, or the project implementors themselves would create whatever access I requested for the sake of illustrating this story. These pathways, as I considered them, were comprised of narrative. I was employing my own heightened literacy in narrative to find plausible connections from point to point, so that the resulting media would yield strong story options when in the editing room. Certainly I was conducting research - in order to tell such a story I needed to learn how these projects worked, how they addressed a certain development problem, what that problem was in the first place, etc etc.
What struck me, however, in experience after experience, was how much the USAID officers, embassy staff, project implementors, and even local participants also learned about their own projects as they accompanied a film crew along these narrative pathways. They had never made narrative connections before, and as a result of tagging along with the crew, they saw things they'd never seen, learned points of view they'd never considered, and discovered connections - technical, social, causative - that they had never previously considered. It turned out that narrative-based research had value even (and especially) for people who already might have been considered experts in the working of a complex system. What if accompanying a film crew became a standard part of briefing officers and participants on a new or proposed development project? What if narrative-based research became a standard part of developing an intervention into a problematic system?
Conducting Research Through Narrative
Moving images can be, and are, used for research purposes already in numerous ways. Surveillance and satellite imagery show us important visual change across time. Countless forms of discrete metadata can be drawn out of time-based media, from facial recognition to audio-to-text transcription on to geotagging location data and even reflexive forms of information regarding the tools used to make the recordings themselves - which are potentially informative to researchers studying the media down the line.
Additionally, 'visual research' is a rich branch of contemporary ethnography and social science work. The use of photography, audio recording, video recording, performance, drawing, and more in the study of complex social and environmental systems has a substantial literature and role in academic study. In particular the use of video as a collaborative or reflexive tool for studying and intervening in a social system has been thoroughly explored in the roughly 40 years since video technology became inexpensive and portable enough to use it as one once used a sketchbook or a still camera.
These uses of the moving image and methods of visual research are components of the narrative-based research methodology, but the core of this form of study will make use of a different form of data. The metadata drawn from the analysis of moving images is often the end of the line in terms of information gathered; a satellite map, for example, shares a set of concrete geographical or environmental information, or facial recognition metadata is highly specific to a single piece of information - they don't extend into causality (why a person is in a place, how the land has come to its present form). Surely there is evidence of this causality, and often analysis of the data is intended to draw out this causal hypothesis, but the data is just a part of a rich matrix of possible narratives.
The difference between these forms of data - quantitative metadata vs 'narrative data' - is partly caused by the difference in perception between a machine and a human being relying on a trained specific literacy. Perhaps at some point in the future machines will be capable of making (often irrational) causal connections between millions of simultaneous inputs.
A common perception of artists is that they are first and foremost producers of objects and experiences. Within the arts and art education, we understand this is rarely the case: rather, artists engage in an inquiry-based form of learning. It is an iterative process not unlike the 'scientific method' of inquiry, hypothesis, experimentation, observation, revision, and reiteration. The data artists employ in this method, however, is distinct, as it is often (but not always) qualitative. Artists working with time-based media are particularly reliant on a sense for causality in and across different milieus - in this they are employing a literacy in narrative. An inquiry is moved forward by a sense that one thing has caused another. We can see this very clearly in the artistic process of the nonfiction filmmaker (but, importantly, we must recognize that it is far from exclusive to this form).
In documentary film production, a filmmaker begins with a question - a problem set to study - and then begins an inquiry through the camera. Filming interviews, surveying landscapes, exploring places, the 'needs' of the camera leads the learning. In microcosm, we must ask why the camera operator pans at a given moment, why they focus on a particular subject at a particular time, why in the midst of a dialogue they move from shot to shot, reframing, recomposing. What are the meanings and origins of these gestures?
They come from a sense of serving the perceived narrative of the situation - a qualitative (but trainable) sense that one instance is about to, or has just, caused another instance. From this narrative reading-and-writing, the filmmaker is able, after sufficient time in inquiry, to construct a story. More importantly, however, they have learned about the problem set in intimate, important ways, and can navigate their subject with an expertise unobtainable in any other way.
In most contemporary documentary film production, however, the 'narrative need' of the camera is really an extension of an audience's need to understand what the filmmaker is experiencing. Knowledge of an eventual audience, and their perceptual tendencies, can drive a filmmaker's process, and shape a story from without, making use of the narrative material of the subject system. This occurs in the act of filming, in the process of coordinating a production (deciding who to talk to, where to film, how long to pursue a narrative line), and in the edit, where visual and narrative literacy is forcefully employed to make coherent narrative 'sense' out of a large amount of audio and video recording. This narrative sense is not always (rarely, in fact) the same as a chronology, or even a clear-cut causal relationship between instances - rather it is a permissive concoction of perception - editors may take liberties with time, place, and content if the resultant sequence can be perceived as making narrative sense. This suggests that this perceived causal connection is a powerful mode of thinking in an audience, and it is similar to the nonlinear but highly causal experience of individual consciousness. Chronology is important, as are protagonists and settings - but our perception of causality, our sense of the narrative within which we live, is profoundly nonlinear and capable skipping from place to place, time to time, 'clip to clip' within the editing bin of our memory and subconscious.
If the pursuit of knowledge through a search for narrative causality can function so well for the construction of consciousness-mirroring film experiences for audiences, then perhaps it can also be used strictly as a tool for the creation of knowledge about a subject system, without the topically agendaed and often commercial outcome of a film for audience consumption.
The tools of film production are made to shape these objects-for-audiences - the cameras, editing software, etc, lead filmmakers to produce narratively linear experiences out of their own multidimensional, nonchronological, nonlinear experience of production. Particularly software editors are designed from a legacy of linear (emulsion- and magnetic tape-based) story-producing tools, and they forcibly shape the inquiry of the artist into a 'sensible' product for the consumption of audiences.
If we start from a new premise - not to produce a story for consumption by an audience, but to gather and synthesize knowledge about a subject-system - we need only make a slight adjustment to the production methodology (opening it up to a non-agendaed pursuit of causal links, possibly more akin to investigative journalism than documentary), and to reinvent the 'postproduction' or visualization tools so that they are less inclined to output a linear sequence of perceived causality that will satisfy the narrative instincts of an audience, and more capable of visualizing the rich multidimensional matrix of perceived causal relationships and motivations that the filmmaker themselves navigated through in production. If a filmmaker (or an artist, in general) becomes a uniquely qualified expert in the subject of their interest through the act of making a film or artwork, than enabling a more complete visualization of their experience would allow an end-user to share in that unique expertise.
A Digital Tool for Narrative-based Comparative Research
Current digital editing software is generally designed from legacy methods, with traditional media purposes in mind. (It was surprising to once hear from an Avid interface designer how the 'moon' icon that famously came to signify the In/Out buttons in that program was actually derived from the shape of the thumbnail of the film editor who once would have been holding a strip of celluloid up before him to determine the length of a shot.) However much software designers alter the interfaces of video editors, they still lend themselves to generating linear sequences of media, and those sequences are inevitably the singular result of an editor's decisions.
A generation of experimental software developed during the first decade of the 21st century aimed to alter this direction, focusing instead on using an algorithmic process to create dynamic media sequences, that is, videos that are in a different sequence each time they're viewed. These may use various viewer inputs or metadata-derived triggers for creating the sequences. Among these algorithmic video editors was the Korsakow platform, developed by Florian Thalhofer of the Korsakow Institute. Similar to Lev Manovich's experiment 'SoftCinema', Korsakow reimagines the user's raw media not as clips in a bin but retrievable, repeatable, and most importantly taggable media assets in a database which can be called upon at any time, using triggers of the users choice - mouseclicks or user-defined or computer-defined algorithms, among them. There is no fixed sequence, but rather branching and diverging opportunities for viewing which may make for a different sequence each time. The act of 'editing' a Korsakow film (or 'K-film') is ultimately restrained - you define the media clips, place them into the database, and then populate them with keywords, which could be thematic, arbitrary, or anything else. The program then creates a viewing environment where the clips play through based on that user-entered metadata, and the 'editor' can make the sequence have as many or as few possible branches as they like, based on the extent of the metadata tagging.
Once it's time to 'exhibit' a K-film, the viewing environment is essentially cinematic - a black frame in a web browser populated by grid-based video screens. One of these screens can be the 'primary' screen, and when viewing a K-film this way it is, when all is said and done, still a legacy cinematic experience, even if we watch with the knowledge that a machine has made the final decision about what is being projected before us, and not a human editor. There is no evidence of the algorithm; and if you only watch a K-film one time through, no awareness of the variability of the sequence.
In a workflow that begins with a traditional editing platform such as Adobe Premiere, Avid, or Final Cut Pro and then goes on from there to use Korsakow as a sequencer, we can combine the curatorial and organizational strengths of the traditional workflow with the open, adaptable, and data-based aspects of working with Korsakow to see relationships between pieces of media - such as potential narratives - that might otherwise not be observable if we just kept all the clips in a bin, as the legacy editors are designed to do. However, Korsakow lacks an appropriately innovative means of visualizing these relationships, other than waiting for them to happen on the grid-screen of the browser, standing in for the movie screen or the television.
Many users of Korsakow have reported the desire to make a 'map' of the relationships between media assets, which is essentially a visualization of the keywords that match between clips. These maps of K-films are inherently two-dimensional, then, because they are just a network of words connected by like-like relationships. If we separate out the meaning of each of those words, though, for instance by categorizing the keywords - places, names, feelings, themes - we can create different maps for each metadata category, and then overlay these maps upon each other and see the potential for a multidimensional visualization of media relationships. For example, one 'map' could represent themes discussed in the video clips, another could represent emotional states, and still another could represent geographical location. Therefore a video clip tagged for it's place, the feelings of its subject, and the content discussed could be thought of as an object in 3-dimensional 'space'.
A new proposed narrative visualization tool would enable placement of clips in just this sort of multidimensional space; the nature of the dimensions could be partially standardized but also partly user-definable. If the content of a narrative research project required particular attention paid to some piece of metadata - i.e. identity, geography, economics, historical information - that could be entered as a desired 'dimension.'
Crucially, video is time based and so static tags and metadata labels can't be accurately applied to whole clips without allowing for some changeability across the timeframe of the clip. (See applying dynamic metadata appendix). A piece of video may begin with one subject and transition to another, or lead from one location to another. Metadata, like the image, is dynamic. If we continue to think about these categories of metadata then as locations within multidimensional space, a clip with dynamic metadata can be thought of as a pathway, leading from one state to another. In fact, it would be a multithreaded pathway, perhaps quite like a neuron or a web-node. There is currently no tool which allows us to visualize media like this, but there are potential benefits to being able to, and they are related to developing a literacy in narrative.
These elongated metadata-pathways, embodied by video media situated in a virtual multidimensional space, can be seen to begin to lead one to another. Pathways will connect to each other, lead away from each other, and form webs of alternating density and scarcity. What these webs of connectivity represent is an important aspect of what we know as narrativity - the perception of causality, the idea that one thing may reasonably or 'logically' lead to another.
Filmmakers, in their capacity as systems-thinkers where story is concerned, are inclined by training and intuition to understand the connectedness of different shots, moments, scenes. Still, the process of shooting and editing is iterative, and often requires trial and error to see if a shot, cut, or scene 'works', or makes narrative sense to a prospective viewer. What a visualization of all the possible narrative pathways within a given set of media offers, is the chance to visually compare the landscapes created by the media. We could almost physically traverse the paths made by connecting nodes - this act of traveling would be seen in two ways: 1.) it would be like navigating the virtual landscape, almost as a video game avatar or flight simulator navigates a virtual space, and 2.) this virtual space would be populated by media assets, which can be playing in an inset screen or separate monitor, and the sequence of media created would be, in effect, the 'final cut' of a film. As we pass each media node, that clip or segment plays back, and seamlessly leads into the next clip as we move or are moved down given pathway.
Because these pathways represent connections in dynamic metadata, we can watch the 'edit' of the media with a critical sense of why a cut or transition in content 'works' or doesn't. Perhaps it was a poorly constructed pathway, one which was founded on a piece of metadata that was only weakly related to the content of the media. It's like watching an action-packed Western, waiting for the love story - relying on the wrong category of metadata (the romantic content) can undermine or seem inessential to the thrust of a 'logical' story to a viewer.
This comparative study of media assets and the categories of data used to map it out will suggest certain pathways as being 'better' than others, in terms of the narrative momentum they carry. Some pathways through a collection of media are simply better stories than others. Many - if not most - of the countless pathways in fact would hardly be recognizable as stories at all to a viewer. They would seem like a somewhat random montage of clips; this tells us they have, in collection, less narrative coherence. As a viewer starts to identify the pathways through a set of media that has the strongest sense of narrative coherence, they themselves begin to learn about what makes narrative. And furthermore, if they identify a pathway that has a strong feeling of narrative coherence, an analysis of the categories of metadata in the clips along that pathway - we propose - will tell us something important about the system being studied.
This would permit a non-filmmaker to iteratively work their way to a narratively coherent sequence of media, and simultaneously derive insights into the forms of metadata - thematic, geographic, etc - that might be driving a system. It would teach them something about what makes narrative sense. It would train them to become narratively literate.
However this narrative coherence - the perceived causality written about earlier - is itself a potentially important piece of metadata.
In any given system there are as many 'narratives' as there are participants. Human beings perceive themselves and those around them as being part of a (generally) coherent sequence of events. Of course this is why 'random' events, like natural disasters or acts of violence or accidents, are so difficult to come to terms with. We rationalize them, and extend our scope of the narrative - sometimes calling in the supernatural or fatalistic philosophical thinking to make sense of the sequence.
What if we could use our narrative literacy, and the visualization tool, to make maps of the many narratives inherent in any system involving human beings? If we are literate in narrative, we can read this perception of causality in the media itself - in what people say, how they act, etc. We can make the 'likelihood of causal connectedness' itself a piece of dynamic metadata, and a narratively-literate 'editor' can apply this metadata to media assets in the visualization tool, and allow it to generate navigable landscapes of the motivations and perceptions of the very participants in a human-centered system.
The production methodology would, of course, need to accommodate the acquisition of media which sufficiently illustrates these multiple narratives - but this is what we do on a regular basis as filmmakers. One might argue that it is the primary pathway through which a filmmaker navigates a context - the stories of those around them (and incorporating their own story - very important). This likely depends on the nature of the filmmakers' work and interest, however the end result is almost always a coherent sequence of images and sounds. (Even when that 'coherence' is deliberately subverted by avant-garde or experimental gesturing, this is the filmmakers' own narrative about themselves and their relationship to their images and their audience thrust into the foreground.)
CONCLUSIONS
What's different about acquiring media for the purpose of illustrating a presupposed story (as in for industrial or documentary production) and acquiring it for research and visualization through the proposed digital toolset?
Both methods rely on the filmmakers' developed literacy in narrative, and their ability to navigate a system through a search for 'story points'. However in industrial production and most documentary production, the filmmaker or their commissioning client knows what story they want to tell, or at least they know what 'message' they want to convey. This knowledge is the seed of the editor's agenda when days, weeks, or months later they work to assemble a coherent sequence. Before filming or gathering media, there is scripting, storyboarding, and iteration of story on paper, meant to add efficiency to the production process, so that only the 'essential' or 'relevant 'aspects of a system are filmed or illustrated.
But if we want to use this literacy for a more open kind of research, one that has no entertainment or communications agenda, but rather for the investigation of a system in search of new understandings, then first we must redefine the product of production. No longer do we need to focus our literacies down to an eventual linear sequence of images and sounds. If we look at the tools available to filmmakers, however, none of them actually permits us to easily develop anything but linear products. So we must design new tools.
Building off the conceptual leaps of SoftCinema and Korsakow to permit new means of visualizing collections of moving image media, and reimagining the production methodology so that it relies only on an open, literate inquiry and not on market- or product-pressure, we can reimagine how the intrinsic data of narrative causality can be extracted from diverse contexts and visualized to potentially revealing effect by filmmakers and artists engaged in process-centered, and not-product-oriented, research.
Narrative, as conceived here, may be a phenomenon of human consciousness, but like other aspects of human consciousness, it can be studied as a discrete science; and not solely by psychologists or neurologists, but by those individuals whose life's work is the understanding and creation of quantitative, irrational, and human forms of knowledge. As humans, after all, this perceptual data is as 'real' a kind of information about the world we inhabit as any more traditional objective or quantitative form of data.