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We’re Going To Lingua Fracta All Over This Post_Reading Notes September 22nd

Okay! Time for a new set of reading notes for a new book, Lingua Fracta: Towards a Rhetoric of New Media. (I have to admit that the title made me giggle a bit).

Image hosted on Giphy.

Image hosted on Giphy.

So, this week’s post is actually in regards to the whole book rather than divided into the two halves of the book since I missed posting last week’s reading notes. >.< I’m going to combine what I had previously in a draft, along with my new understandings. Anyways, let’s begin.

Collin Gifford Brooke, Associate Professor of Rhetoric and Writing at Syracuse University.  Image hosted on his website.

Collin Gifford Brooke, Associate Professor of Rhetoric and Writing at Syracuse University. Image hosted on his website.

One of the first things I want to sort out for myself in terms of this book is Brooke’s re-envisioning of the rhetorical canons (the classical ones are invention, arrangement, style, memory, and delivery) through ecologies – “ecology of code,” “ecology of practice,” and “ecologies of culture.” These three ecologies definitely threw me a bit when I first read them, and continued to do so until we worked through a few examples in class. **There has been another attempt through CHAT to remap the rhetorical canons, which were a part of my reading notes for the spring semester’s Networks course.

“Ecology of code” – “is [Brooke's] designation for the varied communicative and expressive resources we draw on when we produce discourse, regardless of the medium. In other words, both the rules and objects of grammar are located within this ecology, but language is one among many media whose elements participate in it” (48). In a sense, these are the underlying tools upon which ecology of practice is grounded, not just as binary codes, but can also be language components for speech or the digital tools used to create video games. Brooke elaborates on this when he clarifies that, “I suggest that an ecology of code is comprised not only of grammar, but also of all of those resources for the production of interfaces more broadly construed, including visual, aural, spatial, and textual elements, as well as programming codes” (48).

It can be thought of as this:

Binary code as an example of "Ecology of code." Image hosted on the website Inspiration Feed.

Binary code as an example of “Ecology of code.” Image hosted on the website Inspiration Feed.

But, it can also be this:

The tools of video game design.

The tools of video game design. Image hosted on the blog, Game On Podcast.

“Ecology of practice” – “Practice implies conscious, directed activity, the explicit combination of elements from the ecology of code to produce a particular discursive effect” (49).  *this ecology gave me the most trouble, especially when we were asked to choose images of what each of the ecologies would look like (I may have blanched a bit in-class).

 As an early example in chapter 2, Brooke uses the ideas of a “Revitalized understanding of canons” as an insight into his idea of “ecology of practice” since the “canons supply a framework for approaching new media that focuses on the strategies and practices that occur at the level of interface” (28).

“Ecologies of culture” – “it is this category that operates at the broadest range of scales, from interpersonal relationships and local discourse communities to regional, national, and even global cultures. Any act of discourse is going to be constrained in various ways by cultural assumptions; similarly, such acts intervene simultaneously at several levels” (49).

So why attempt to revamp rhetoric into ecologies? What is wrong with the traditional canon? Brooke says that he is presenting these ecologies as a way to help “evolve” rhetoric and the aims of rhetorical scholars because “The elaborate dance of competition, cooperation, juxtaposition, and remediation that characterizes our contemporary information and communication technologies has rendered obsolete some of our most venerable models for understanding today’s rhetorical practices” (28). By drawing upon the canons, Brooke seeks to build a new vision of how they work within the digital world and within new media, rather than simply recasting the same terms. The metaphor of the ecology is also very interesting because an ecology is not static; it is organic and adaptive, something rhetorical canons need if they are to stay relevant to the needs of present day rhetoricians and their audiences.

One really interesting point made in the section regarding rhetorical canons was when Brooke alludes to Sven Birkerts and his prediction of the “flattening of historical perspectives” in the sense that “we will cease to exercise history because we will rely on that which is stored in databases” (31). In his response to this death-of-memory prediction, I think Brooke does a nice job of pointing out that digital databases enhance our cultural memory rather than merely threatening to wipe out our interest in historical perspectives.

Death of memory in favor of database archives? Image hosted on the website Baen.

Death of memory in favor of database archives? Image hosted on the website Baen.

So how does Brooke remap the rhetorical canons?

To grant the classical rhetorical canons (invention, arrangement, style, memory, and delivery) more relevance in a digital world, Brooke’s modified canons look like this:

Invention —> Proairesis

Arrangement —> Pattern

Style —> Perspective

Memory —> Persistence

Delivery —> Performance

 Okay, so one at a time:

Invention as Proairesis

Brooke’s re-conceptualization of invention as proairesis makes a space for digital technology as part of the reading/writing/creation/distribution process, giving readers of digital content as it does to those who write the content. Much of his analysis deals the “difference between seeing media such as those listed [in the chapter] as spaces that enable peer-to-peer interaction and conversation and seeing them as media that transform the nature of conversation or even participate in it” (82), but more on that after some vocabulary words.

hermeneutic model of invention – “relies on the relative sturdiness of a final object and the negotiation of meanings within it….When the final products of our invention are judged, in part, by their solidity or sturdiness, it makes perfect sense that we theorize invention to arrive at such goals” (68). It “operates through the establishment of an enigma, void, or mystery– an absence — that will be filled eventually, but is held in suspense… [and] marks the goal(s) towards which the reader (and the plot and characters) are headed” (75). Hermeneutics can be seen as “resolution or actualization,” and, when placed on the level of theory, “simply assumes systematic enigmas, such as the establishment of genre or the demonstration of a theoretical insight” (76).

proairetic model of invention – this term is used by Barthes “to indicate actions or events,” “empirics” (75). Seems to deal with possibilities, rather than resolutions. This term makes the most sense when Brooke brings up the example of a Google search: “One way we might treat Google proairetically is simply to resist the closure implied in search ‘results’ and to treat that page as a point of departure, even and especially when the results are mixed. The results of a given search provide users with pages and pages of links, of departure points, that bring potentially distant topics and ideas into proximity both with each other and the user” (83). He broadens this out to discuss social bookmarking websites that allow users to create bookmarks, but then also follow the threads upon threads of bookmarks created by ALL users on the site: “The addition of each bookmark changes the site, reinforcing certain connections, adding new ones, and expanding the network in small but important ways. It enables a process of associational research and exploration that resists closure” (85).

Brooke’s final definition of this term: “a focus on the generation of possibilities, rather than their elimination until all but one are gone and closure is achieved. Closure is no less important than it has ever been, but with the advent of new media and interfaces that resist closure, proairesis provides an important corrective to the hermeneutically oriented inventional theory that has prevailed in our theory to date” (86). It’s fascinating that the emphasis is on the inclusion of possibilities rather than slowly weeding them out.

No longer require the Highlander slogan. Image hosted on We Know Memes website.

No longer requires the Highlander slogan. Image hosted on We Know Memes website.

**As a side note, I would not Google this word. I made that mistake since Brooke does not offer a concrete definition for this word (he focuses more on hermeneutic), and found that proairesis is not considered a Scrabble word, though it is worth 12 points in Scrabble and 13 points in Words with Friends.

kaironomia – “an inventional practice that locates itself not within repetition (the demonstration of topoi) or difference (the myth of the ordinary genius), but in the dynamic of the two,” which represents a “contradictory injunction” (77)

virtualization – Levy’s term for “the opposite of reading in the sense that produces, from an initial text, a textual reserve and instruments of composition with which a navigator can project a multitude of other texts” (qtd. in Brooke 80) <— Brooke notes that, “It is the human-machine interaction that makes for virtualization” (81)

Brooke works to decouple the vision of invention that scholars like Sven Birkert put forth an illusion that acts “of reading or writing can be fully divorced from [their] context” (73). Birkerts’ concept of the relationship between reader and writer with the text in the middle– “We might reach a more inclusive understanding of reading (and writing) if we think in terms of a continuum. At one end, the writer — the flesh-and-blood individual; at the other end, the flesh-and-blood reader. In the center, the words, the turning pages, the decoding intelligence” (qtd. in Brooke 72)– might look like this:

The start(?) of the invention continuum: the writer. Image hosted on Teen Life Blog.

The start(?) of the invention continuum: the writer. Image hosted on Teen Life Blog.

At the end(?) of the continuum: the reader. Image hosted on the blog Writing and Rambling.

At the end(?) of the continuum: the reader. Image hosted on the blog Writing and Rambling.

Such a model doesn’t quite hold up, even when viewed with print as the medium. In the age of hyperlinks and greater collaboration that comes with digital communications, Birkert’s model feels heavily lopsided, something that Brooke addresses by drawing, again, upon LeFevre: “invention is not simply the process by which a writer creates a text whose meaning is received by a reader. The ecology of invention includes the practices of writing and reading, but the relationships among those practices are not closed, idealized, and privatized transactions” (74). There is no bubble in which writers and readers exist, especially as the internet connecNetowts us all outwards to information and other people.

This graphic seems more appropriate. Image was created by Collin Gifford Brooke and hosted on his website.

This graphic seems more appropriate. Image was created by Collin Gifford Brooke and hosted on his website.

This site did a nice job with their video discussing Karen Burke LeFevre’s “invention as a social act”: http://ccdigitalpress.org/nwc/chapters/garrett-et-al/a1s3.html

Arrangement as Pattern 

Brooke starts off the chapter devoted to Pattern by focusing on the claims by earlier scholars that the rhetorical canon of arrangement fell to the wayside during the advent of hypertext culture as hyperlinks did not privilege one path over another and the viewer’s decisions rendered any intentions by the author as useless. Brooke, though, counters this statement: “The links that allegedly demonstrate the irrelevance of rhetoric are rhetorical practices of arrangement, attempts to communicate affinities, connections, and relationships” (91). One of his aims is to move away from the “traditional understanding of arrangement as sequence” towards a conceptualization of “arrangement as pattern”  and to reveal that “the issue is not whether arrangement predates our textual encounters, but rather what practices we might develop with new media to make sense of them” (92).

For arrangement to be understood in regards to New Media, the division between spatial and temporal must be understood “that every technology gives us not only a different space, but a different time as well” (93). So let’s break this down a bit further.

An expectation, according to Darsie Bowden, that we have for print texts is “containerism, a set of metaphors that posit the discursive space of writing as a container into which we pour content (from the containers that are our minds),” which houses “an in/out distinction that corresponds to our notions of subjectivity and identity and, as such, appears quite natural to us,” though the text is considered “generic until it is filled with content and achieves some sort of meaning” (93-94). However, containerism fixes the concept of arrangement, seeing spatial elements in a print text to be linear and sequentially instead of seeing the space for possibilities of other arrangements (though we are not bound to read everything sequentially since we can skip around in a book: read the conclusion first, a middle chapter before a beginning chapter, and so on).

Containerism - asking us to let ourselves be contained by the text lest the text fails and we become disoriented (Brooke 94). Image hosted on the blog De la Course des Nuages.

Containerism – conditioning us to be contained by the text lest the text fails and we become disoriented (Brooke 94). Image hosted on the blog De la Course des Nuages.

In order to explore how New Media and digital spaces help us to re -conceptualize the spatial, Brooke draws upon David Weinberger and the idea that the meat-space is a container from which web-space is then filled, though I think this relationship goes two ways now with the meat-space being transformed, in a sense, by the digital space.

In terms of arrangement, though, Weinberger describes the digital space with a “sense of place that creates its own space,” with it being active rather than passive (qtd. in Brooke 95). This reminds me of an example mentioned earlier regarding social bookmarking. For every bookmark created, the threads of the site expand outward as there is more content within the site. The same for this blog. For every post I write and publish, the “space” of my blog gets bigger as the posts create an extending line of content. The posts do not have to be read sequentially, especially since many of the posts are about different texts and only truly operate under an overarching theme (usually networks). And this is where the move from arrangements to patterns comes in. Brooke brings in David Kolb and his suggestion about “a number of intermediate forms (cycles, counterpoints, mirror words, tangles, sieves, montages, neighborhoods, split/joins, missing links, and feints), patterns that demonstrate a wide variety of rhetorical effects that are possible if we think beyond the container model” (96). For Brooke, to understand how the rhetorical canon of arrangement can blossom in New Media and the digital era, we have to not limit our perceptions within boundaries, even if it seems the most convenient; instead, he turns towards Manovich’s database as an “infinite flat surface” (97).

So how do databases play into arrangement as patterns?

Brooke looks at how Manovich compares narrative and databases, with the example being Amazon. The online shopping site’s way of showing consumers items that had been purchased by others who had also bought the same initial item, the browsing/purchasing history of the consumer, and similar items that are available for purchase are part of a database for the site, but can also be threaded together to make simple narratives. What is interesting is the description of databases that follows soon after: “Although databases may contain no predetermined order, they are useful to us the degree that they provide some sort of order when they are acted on by users” (101). With this in mind, Brooke expands on the Amazon example: “It would be hard to extend a user’s encounters with Amazon into something resembling a full-fledged narrative, but at the same time, the site is designed to respond accurately and meaningfully to such encounters — a response that is not accounted for in descriptions of database that stress its utter randomness” (101). Because the website services thousands and thousands of people, creating patterns out of their purchasing and browsing histories, much like an underlying web of code that sorts through the data.

My brain hurts just thinking about this. Image hosted on Tumblr.

My brain hurts just thinking about this. Image hosted on Tumblr.

How does arrangement fit as patterns? It is through associations: “The patterns that emerge are sets of associations among texts that the site reinforces through visibility, potentiality becoming less contingent or temporary as future visitors act on the recommendations generated at site” (103). As each person uses the Amazon site, more connections are made through the data being collected, building associations that return back to the site through algorithms to increase its effectiveness. These associations, though, also create relevancy, allowing a hierarchy of those patterns being chosen over ones that are being excluded  through users’ choices. Exclusion is just as important as inclusion. To bridge the gap between narrative and database, Brooke uses the word collection as it is the “individual assembly of a large group of whatever items we might choose to collect” (109). These collections gain meaning for individuals but start to lose their context outside of that individual’s relationship to the collection, rendering that particular narrative insubstantial or altered to another individual: “The more intimately we are involved in the assembly of a collection, the more likely we are to perceive it incrementally and narratively, while different patterns may emerge in a casual encounter of someone else’s collection” (110). For instance, my anime collection has a history of which I know, with certain titles being picked up at different points in my life. To those who know me best, my anime collection means something beyond VHS and DVDs on shelves, but for those who know little to nothing about me, all they would see are a random collection of Japanese “cartoons.” The same can go for my research or my Amazon purchasing history. The patterns that appear, whether directly or subtly, are Brooke’s new form of the rhetorical canon of arrangement, but this remapping allows code and algorithms into the process, making it not just a human endeavor but a human-machine endeavor.

Style as Perspective

Whew, on to the third remapped rhetorical canon: style as perspective. This seems to be one of the more popular canons for New Media as Brooke declares that, “to speak of media is to speak of forms of expression, the traditional province of the canon of style,” emphasizing the relationship of the visual and verbal, especially in regards to how this relationship changes when “consider[ing] what style might look like when we consider it in terms of interfaces rather than static texts” (113). To be honest, the first thing that pops into my head when reading the start of this chapter look like this:

A very scholarly way to imagine initially the relationship between the visual and the verbal, no? Image hosted on Giphy.

A very scholarly way to imagine initially the relationship between the visual and the verbal, no? Image hosted on Giphy.

Yes, yes I did just include that in my reading notes. And yes, it is time to move further into style as perspective. Now Brooke seems to have chosen the word “perspective” because it offers two means, which he quotes from Keither Moxey as being “either one point of view among many, or the point which organizes and arranges all others” (qtd. in Brooke 114). This is interesting because when we think of the style of a book, something that can be seen as a static text, and we see the style, whether linear in a traditional sense or multi-layered (like the book First Person) or  even in a more random-seeming style (House of Leaves), there is a sense of permanency to the style of the text. Within a digital space, there is the feel of possibilities, though the more I work within digital spaces, the more I feel the constraints of the spaces within which I am working (a nod to WordPress and the limitations of the text box). Brooke calls for the readers to change the concept of “visual rhetoric” to “visual grammar,” and he “draw[s] on Friedrich Nietzsche to suggest that we restore style to its place in our ecology of practice, rescuing it from its classical banishment to the ecology of code” (114).

Mary Hocks, in her work “Understanding Visual Rhetoric in Digital Writing Environments,” lists three features for visual rhetoric in the digital media:

-Audience stance

-Transparency

-Hybridity

Brooke takes a step back to understand how we talk about style now, especially in terms of teaching students to write: “Our contemporary understanding of style treats it as sentence-level syntax, catalogs of tropes and figures, and commonplace injunctions (e.g., avoid the passive voice; use specific, concrete language), reducing it to a series of localized, conscious choices” (116). After much meandering through Aristotle and his influence on the reduction of style, Brooke returns to perspective, stating that it is “a method for displaying three-dimensional objects and/or scenes on a two-dimensional space. Much like the technology of writing exteriorizes the reader, perspective presumes a viewer whose physical position mirrors the vanishing point” (120). This gears style, in the digital era, towards transparency. To develop this further, Brooke links to Don Idhe’s “description of the physical, perceptual process of reading…distinguish[ing] between microperceptions, which are and/or sensual, and macroperceptions, which are hermeneutic and/or cultural. The structuring (or disciplining) of perception marks a transition from microperception to macroperception; in other words, the transparency of the printed word renders our physical perceptions of the text, as we are reading at least, minimal to the point of nonexistence” (121).

This is what comes to mind every time I read the word transparency in relation to reading. Creepy, though. Image hosted on the website

This is what comes to mind every time I read the word transparency in relation to reading. Creepy, though. Image hosted on the website Frank Minnaert.

Moving from the transparency of writing, Brooke explains that, drawing upon Lanham, “Language on the computer screen, in contrast, is subject to many different kinds of transformation by the user (size, font, color, layout, etc.) that Lanham argues we are often encouraged to consider the textual form as expressive. With electronic text, he explains, we often toggle between looking through text and looking at it” (132). Transparency is no longer an issue, with the language being part of the experience instead of the backdrop. It was interesting (and quite within the scope of my research) that Brooke brings in an example of World of Warcraft and the interface the players’ interact with during gameplay, especially when players can customize the interface themselves, allowing them greater immersion into the experience if they so choose (there are options to render the game to basic elements, stripping the visuals down to necessities).

Memory as Persistence

And so memory moves to persistence. In this chapter, Brooke moves beyond seeing memory in the digital era as merely storage on our computers, as well as physical texts as extensions of our memories. Instead, he turns to Jacques Derrida (a.k.a. philosophical rock star) to help discuss archives: “[he] writes of the effects that changes in archival technology have on both what is being (and can be) archived, as well as on the people doing the archiving” (144).

Mixing of archives and human minds, plus a dash of Sherlock Holmes for the ride. Image hosted on Tumblr.

Mixing of archives and human minds, plus a dash of Sherlock Holmes for the ride. Image hosted on Tumblr.

To start his remapping, Brooke discusses Plato’s resistance to writing, believing that reliance on written texts would break down the strength of people’s memories because they could then use writing as a kind of crutch (as compared to orality when they would remember longer speeches and poems), while also raising the question “of whether knowledge is located inside or outside of the knower” (145). Within this framework, a presence/absence dichotomy arose. Plato’s belief still lingers, but we have moved far beyond oral culture, with our collective memory finding its place across various forms of media (written, visual, audio, film, and now into the digital spaces like the Cloud). One of the most fascinating points in this chapter is in regards to what we archive: “The binary of presence/absence reduces memory to a question of storage, with little thought given to the effects that various media might have on what is being remembered” (147).

Digital archive. Image hosted on the website Electronic Portfolios.

Digital archive. Image hosted on the website Electronic Portfolios.

Brooke explains a shift away from only using the presence/absence binary by N. Katherine Hayles in her book How We Became Posthuman: “Hayles suggests a ‘semiotics of virtuality’ that maps phenomena along two different axes: absence/presence and pattern/randomness” since presence/absence cannot capture the essence of online activity for both the user and his or her avatar(148). To develop this further, Brooke brings two Greek words, Chronos and Kairos, to understand why his drawing upon Hayles’ patterning and randomness:

Chronos “is the artificial patterning of time, its divisions into equal, measurable segments — the time by which we set our clocks and watches, conduct our classes, and organize our history…[and] represents our triumph over time as a cultural achievement” (149)

Kairos “is the time sense at the other end of the spectrum [from chronos], the opportunities that emerge to be seized in a particular situation, unrepeatable and unsystematizable…It is the unwillingness of the kairotic moment to submit itself to our control that has led to its ‘neglected’ status in rhetorical theory” (149)

 With pattern and randomness, there can be randomness (kairos) until a pattern begins to emerge (chronos). However, the reverse is also possible, with moments of chaos occurring in the midst of a pattern. These two happenings alter the perceptions of the the events, the data, the images, and so on. When a pattern emerges out of chaos, it is hard to return to see the chaos again, but the same can be true for when a pattern is disrupted.

When I think of patterns emerging, I think of these pictures where the viewer has to locate the hidden faces. Image hosted on Psychlinks Self-Help & Mental Health Support Forum.

When I think of patterns emerging, I think of these pictures where the viewer has to locate the hidden faces. Image hosted on Psychlinks Self-Help & Mental Health Support Forum.

Brooke looks at the canon of memory as pattern to build the conclusion that pattern is an ecology of practice, granting it a new space in the digital era beyond merely being relegated to storage. It here where Brooke justifies his reason for transforming memory into persistence with the “construction (and dissolution) of patterns over time” (151). This persistence becomes increasingly important when users are faced with the overload of data that is presented by others and constructed by them on the internet, especially with the Cloud becoming an integral part of how people handle and store data. In the final section of the chapter, Brooke discusses how websites deal with this issue through feed readers or aggregators, which “check weblogs and keep track of whether a particular user has accessed the most recent content. They check our blogs so that we do not have to, in the same way that most mail programs can be set to inform a user when there is a new mail in the inbox” (158).

So how do aggregators feature into memory as persistence? Brooke identifies two types of aggregators that he personally uses: Google Reader (GR) and the memory practice of persistence of cognition.  For him, Google Reader provides a “centralized portal” that “distributes [his] memory, freeing [him] from the need to remember each site individually” as well as tracking basic information trends in his viewing/reading (160). Persistence of cognition is his phrase for a reading and memory practice that springs out of the connection between smaller pieces (such as keywords): “Skimming requires a reader to be able to piece together information in ways that are good enough to gauge a text, perhaps without arriving at a full representation of it” but also “names the presence of particular pieces — certain themes persist across a set of texts” (156; 157). My favorite quote from this chapter, though, comes at the end when he describes our relationship to memory and information: “We take in information, sometimes without being aware of it, and only notice when the information connects with other data to form a pattern worth investigating…Our minds are not simply sites of storage; they perceive connections and patterns that may only become present to us in the later stages of their construction” (166).

Delivery as Performance 

Woot! Woot! Last rhetorical canon to be remapped: delivery as performance. Brooke lists two ways in which delivery is defined that are relevant to rhetoric: 1) as a transitive process, and 2) as a performance (170). With this remapping, Brooke brings up terms like DeVoss and Porter’s “economies of writing” and Trimbur’s “circulation of commodities” with regards to delivery of content and how aggressively some companies/organizations will try to restrict the distribution of their content (172-173): “It is difficult to imagine that corporate producers are particularly worried about audience production of content, for example, when we consider the heavily embedded technological, cultural, economic, and medial advantages that the various culture industries possess. If reflect on how heavily these corporations are invested in distributive control, both directly and through the management of consumer attention, it is difficult to see their aggression in prosecuting ‘bad users’ as anything other than an overreaction” (172). This makes me think of people who create fan-made anime music videos (AMVs) on YouTube (much like the one I have linked at the bottom of this post) and how their videos are sometimes (not always in a majority of the cases) removed despite the creators attributing ownership of both the songs and the clips/artwork to the rightful owners. The creators of the AMVs are not receiving compensation for their work, nor are they claiming ownership of the original content. Their videos are purely for entertainment and are a large part of fan culture’s tributes to a series, a character, a couple, and so on, yet some companies see them as violations of copyright.

Now that I am done with my tangent, rewind back to the discussion about circulation and distribution as part of delivery. Brooke links this discussion to Timbur again with Timbur’s comment on “how the act of translation necessarily participates in and shapes the circulation of biomedical discourse in ways that go beyond simple information transfer” (qtd. in Brooke 174). It is here where Brooke pulls in “delivery as medium” to stop the perception of circulation to be aligned with the perception of simple transmission (rhetoric should not, in this view, remain static between media) (174).

Information being circulated among media should go beyond the simple transmission of information. Image hosted on the site for Newcastle Libraries Online.

Information being circulated among media should go beyond the simple transmission of information. Image hosted on the site for Newcastle Libraries Online.

But that is delivery in the terms of a transitive process, so let us take a look at delivery as performance. What does this mean in a digital era? Brooke turns towards the concept of ethos (character, or credibility) in regards to a person’s work (for example, a student like me who is trying to create content online in a public space not just for my teacher and peers, but also for anyone who visits the blog and lingers long enough to read this far). There is the understanding that information from the interwebs must be evaluated deeply to be sure that the information is accurate, the source is credible, and the author is not some hack (and there are plenty of sites where such concerns seem to the lowest priority). However, Brooke pushes forward a little further with his comment about technology’s role in the process: “The underlying assumption of these evaluation checklists, however, is something that we should find more problematic. Put simply, much of the advice for evaluating Web-based information posits credibility or ethos as a quality that is decontextualized from the technology, an attitude toward delivery that sees it simply as transmission” (184). Brooke notes that the credibility of websites is based on their connections to the “real world” (or meat space), which is what I am doing here by citing from a physical book being held in my arms as I type this sentence; anyone could pick up a copy of Brooke’s book and check the passages that I am citing.

To push back against this notion of credibility as tied to how we have evaluated books, Brooke uses Wikipedia as example as it is open to users to edit and add content, even if those users are not certified experts in their fields. The content being added is evaluated for its content and actions taken against users who prove to add false information or prove less than credible as sources, but the openness of the adding/editing process is changing how we perceive and understand encyclopedias, even though Wikipedia is not free of criticism (188).

Encyclopædia Britannica. Image hosted on Wikipedia.

Encyclopædia Britannica. Image hosted on Wikipedia.

Wikipedia as an encyclopedia. Image hosted on the blog Southern Lifestyle.

Wikipedia as an encyclopedia. Image hosted on the blog Southern Lifestyle.

While Wikipedia is not to be seen as a site for pure credibility, Brooke looks to it as a site of discourse for issues of authorship and credibility. The site offers what a place where credibility becomes a performance, a practice, messy as that can be at times “represent[ing] the kind of opportunity that traditional encyclopedias can never dream of providing — an ethos that is interactive, democratic, public, and, at times, contentious” (191). It is interesting to think of credibility as a performance, but his example about the credibility of Wikipedia as burgeoning with its members really strengthens my understanding of the concept.

And so ends this round of reading notes. Fare thee well, Brooke and your remapped rhetorical canons for the digital era.

Fist bump for making it through this mad tangle of notes. Image hosted on Rebloggy.

Fist bump for making it through this mad tangle of notes. Image hosted on Rebloggy.

Nothing to see here, folks. Image hosted on Giphy.

Nothing to see here, folks. Image hosted on Giphy.

Citation

Brooke, Collin Gifford. Lingua Fracta: Toward a Rhetoric of New Media (New Dimensions in Computers and Composition). Cresskill, NJ: Hampton Press,  2009. Print. 

Skipping Along through New Media

 

Update: As part of our reading notes assignment, my classmates and I are to make comments on two peers’ posts every week. So, here are mine:

Chvonne’s post

Chvonne’s post did a really nice job of dealing with the second half of Brooke’s text, especially the way she brings him to task for not fully delving into the messiness that comes with the ecologies of culture. I think Chvonne raises a good question (one that made me stop and think for awhile) about whether or not there are practical ways to apply Brooke’s remapping of the rhetorical canons. The conclusion that I finally came to was that for the generation of students who are now entering college, it may benefit them to use their foundational knowledge of computers (since this is a technology they have grown up with) as a way to understand rhetoric, rather than to approach them first with rhetoric to understand how the digital era is changing our perspectives. These students are growing up with connections through Facebook, seeing first hand how social spaces like Twitter are sites of social activism as well as sites of public shaming, and approaching archives not as physical spaces but as data that can be accessed anywhere at any time with the advent of Cloud computing. For them, rhetoric of Socrates and Plato is an archaic past compared with how rhetoric is now being reshaped to fit the needs of a digital era (just as it had changed for television and film).

 


Case Study #4: FrankenTheory

Boundaries in My Analysis of Google Analytics

I am limiting my analysis of Google Analytics as an object of study by focusing on its activities and its data model as reported in terms of dimensions and metrics.

  • Google defines Analytics activity as collection, collation, processing, and reporting.
  • Google describes its data model as consisting of user, session, and interaction.
  • Google collects and reports data in terms of dimensions (“descriptive attribute or characteristic of an object”) and metrics (“Individual elements of a dimension that can be measured as a sum or ratio”) (Google, 2014).

These limits and terms are described in detail in my earlier Re/Proposed Object of Study: Google Analytics blog post.

I chose GA as my object of study because it’s a tool with which I work on a daily basis. I proposed GA as my object of study to my boss, the director of our school’s marketing and communications team, before formally proposing it in class because I wanted approval to use our school’s GA account in my study. I also expected my study to contribute to my understanding and use of GA in web development and management. A deeper understanding of GA as a network has provided both a tool for theoretical exploration and practical application.

Here’s an example of how applied this theoretical study has become. On April 16, with little fanfare, Google announced that it was replacing the term “visit” with the term “session” in its reports. I missed the announcement entirely, so I was surprised while measuring the result of online advertising efforts in our campus newspapers to discover that the “unique visits” metric that I had been using was no longer available; instead, it had been replaced by the “sessions” metric, without the “unique” modifier. I was also surprised to discover that the “unique visits” metric I had been using did not match the “sessions” metric when I re-ran prior reports to test data accuracy reports; “sessions” reported higher numbers than “unique visits” had reported. As we reached the first of May, when I normally complete April reports, I realized the full extent of the terminology change: “unique visits” were no longer being measured. Two plus years of reporting data were potentially compromised as inaccurate, since we report data for month on month and year on year comparisons (e.g. does April 2014 look better than April 2013 in terms of overall unique web visits, and does the calendar year-to-date period of January-April 2014 look better than the previous January-April 2013 period?).

As a result of my study of the structure and function of Google Analytics, I had learned how GA counts session data. Critical inquiries had questioned whether GA’s reporting of unique visits could be accurate given the browsing patterns of today’s web visitors. Visits (now sessions) are defined as individual browsing sessions on a given website on a given browser and platform. A visitor (now user) who visits the same website using two different browsers (Chrome and Firefox, for instance) would be calculated as two unique visits (when unique visits were provided) because the session is browser specific. Furthermore, a visitor who visits the same website on a desktop platform browser, then revisits the same website on a mobile device, would be calculated as two unique visits, because the session is platform specific. In short, “unique visit” is really a calculation of “individual session” without a distinction of uniqueness of the visitor. Using the term “unique visit” suggested (and my marketing team and I took it to mean) visits by unique users, a measurement we considered superior because it suggested the actual number of visitors. What we should have been measuring, however, was visits, regardless of their “uniqueness,” because there was no unique quality to the visit in terms of the visitor. The end result is that I will need to re-record our historical data in terms of sessions rather than unique visits, potentially revealing visit patterns we had not before seen or understood.

Without this study of GA as a network, I would not have understood why reporting data did not match, and I would have struggled to find documentation of the issue. There remains little documentation from Google itself about the disappearance of unique visit as a reported metric as of this date. In short, the application of my theoretical exploration directly benefited my and my team, and ultimately our school and our understanding of our data within the framework of industry benchmarks.

Theories of Networks and Google Analytics

I’m using two theories — Castells’ network society and Deleuze & Guattari’s rhizome — to flesh out my understanding of Google Analytics and sketch out my Frankentheory of a network.

First, here’s a review of some familiar territory: My application of Castells’ network society to GA from Case Study #2. I’ve brought this in as a piece rather than linking to it because I’d like to make departures from specific aspects of this application in discussing Deleuze & Guattari and in sketching out a Frankentheory.

Defining Google Analytics

Castells (2010) considers technology to be society (p. 5). As a result, GA can be considered social. As an information technology, GA creates active connections between websites (data collection), Google data centers (data configuring and processing) including aggregated tables (processing), and GA administrator accounts (configuring and reporting). These active connections collect, mediate (configure and process), and report on the three aspects of the GA data model consisting of users, sessions, and interactions. These connections represent social actions. So Castells (2010) might define GA as a global informational network (p. 77) that collects data from and reports data to local nodes (websites). Google servers where data are configured and processed might be considered mega-nodes (xxxviii) that, through the iterative process of increasing user visits and interaction by improving website design and content based on GA reported results, impose global logic on the local (xxxix).

Nodes in Google Analytics

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Google Data Center Locations: Image from Google Data Centers.

Individual websites, GA account administrators, and website visitors are local nodes in the global informational network. Google data center servers are mega-nodes in the network. Google employees who program GA and maintain Google servers and centers are localized nodes in the global network. Google’s data centers are located in a variety of locations that include North America, South America, Europe, and Asia. Several are found in Castells’ (2010) “milieux of innovation” (p. 419) including Taiwan, Singapore, and Chile. Others are found in what appear to be unlikely global spaces, including Council Bluffs, Iowa, and Mayes County, Oklahoma. These locations reiterate Castells’ insistence that local and global are not mutually exclusive polar opposites; rather, the new industrial system is neither global or local, but a new way of constructing local and global dynamics (p. 423). Websites, administrators, visitors, servers, and employees are simultaneously localized nodes (even the the mega-nodes are situated in space and time) in the global informational network.

Agency among Google Analytics Nodes

GA account administrators and website visitors have the greatest level of agency in the network, while Google employees exert limited agency within the confines of their labor relationships and conditions. Account administrators would likely be considered among Castells’ (2010) “managerial elites” (p. 445), while Google employees who maintain and program the servers might be part of Castells’ disposable labor force (p. 295). Account administrators have the authority to configure GA data, including the ability to filter out results, narrow data collection according to metrics and dimensions, and even integrate external digital metrics in GA. This authority is not, of course, the authority of Google’s corporate structure and hierarchy, but within the boundaries of GA data model and activities, account administrators exude authority. Website visitors may choose to visit, or not visit, any given website, once or more than once (meaning a single session or multiple sessions). This agency includes the power to intentionally separate themselves from the network, meaning that, for users, they only enter into the network as a node when they visit the tracked website. Interestingly, only the GA administrator has authority to eliminate users from the network; account configurations may filter out visitors along several dimensions.

Nodal Situation and Relation

Nodes are locally situated. While simultaneously part of the global informational economy, all of the nodes in the GA network are situated in a space and time. This simultaneous here/there compression of space and time is the origin of Castells’ (2010) “space of flows” (p. 408) and “timeless time” (p. 460). Websites are simultaneously hosted on physical servers around the world and locally viewed on specific platforms and media. Users are simultaneously accessing global data in territorial space on hardware. GA administrators are situated while configuring accounts and loading reports from the cloud. Google data centers are situated in specific locations, but they collect and process global data from local spaces and times. Google employees are culturally and territorially situated in the global Google labor pool.

Data rarely travels along parallel paths in the GA data model or GA activities. Website visit data are collected in the data modeluser, session, and interaction data — and sent to Google data centers for processing and configuration. Other than writing unique user identification data onto cookies on users’ browsers or apps, little data travels from GA to users. Website content is indirectly affected by GA reports configured and read by GA administrators, but within the GA activity network, websites are unaffected by GA activity on the data model. Beyond the boundaries of the OoS, of course, Google serves plenty of data, in the form of ads, back to users. But that’s now beyond the scope of this study.

Movement in the Network

Framework for Movement: Wires in The Dalles, Oregon, Google Data Center. Photo from the Google Data Center Gallery.

Data moves in GA. More specifically, data in the GA data model moves in GA. Data are initiated by users visiting tracked websites. Specific frameworks must be in place for connections to occur and data in the data model to be collected. Namely, websites must contain GA tracking code, embedded in the website code through the agency of the GA administrator. The embedded GA tracking code enables, and the web browser and hardware afford (Norman, n.d.), the user to initiate a tracking pixel (gif) and generate data to be collected in the GA data model. Once collected, the data are configured (by the account administrator and by the GA algorithms), processed (in a largely opaque manner) and collated in aggregated data tables, and reported in visual and tabular representations. In Castells’ (2010) terms, data represent flow in the GA network (p. 442). That data is both spatial and temporal (it comes from and is attached to a specific territory and represents a specific, chronological activity), but it is also entirely global and digital.

Content in the Network

Data are collected and packaged — literally, in a gif image pixel — in parameters relating to user, session, and interaction. The GA tracking code encodes data and sends it to Google data centers where the data are decoded, configured based on administrator preferences, processed and repackaged in aggregated data tables, and made available to the account administrators. The reporting function remediates the data in visual and tabular formats for ease of reading and use. While the data reported are considered authoritative and authentic, the actual processing function remains largely proprietary, with only end results available to extrapolate what processing actually occurs. This black boxed processing function seems unlikely to represent Latour’s (2005) intermediary; as Fomitchev (2010) claims, there are probably processing functions that result in highly mediated, possibly even inaccurate, results. Castells (2010) would likely measure GA performance based on “its connectedness, that is, its structural ability to facilitate noise-free communication between its components” (p. 187). I hope we will see increased academic scrutiny focused on this perceived intermediary function in GA, even as we scholars rely on its results.

Birth and Death of a Network

Killing the Network: Failed Google data hard drives to be destroyed at the St. Ghislain, Belgium, Google Data Center. Photo from the Google Data Center Gallery.

Castells (2010) indicates that global informational networks emerge within milieux of innovation. These main centers of innovation are generally the largest metropolitan areas of the industrial age (p. 66), able to “generate synergy on the basis of knowledge and information, directly related to industrial production and commercial applications” (p. 67), and combine the efforts of the state and entrepreneurs (p. 69). Nodes on the network get ignored (and therefore cease to be part of the network) when they are perceived, by either the network or by its managerial elites, to have little value to the network itself (p. 134). The GA network grows as more nodes are added, either as users or as web pages with tracking code. GA administrators have agency to kill network nodes by removing tracking code from pages, or by directing IT managers to remove poorly performing web pages. Users have agency to quit visiting a website, thereby removing its value to the person. While many other actions by agents outside the GA network may affect the growth or dissolution of the network, they are outside the boundaries of the GA activity and data model.

And Now, the Rhizome

First a note about using Deleuze & Guattari. I did not enjoy or particularly “get” this reading the first time around. I grasped the broad strokes of the argument, but this is a chapter that requires close, multiple readings. What I discovered as I re-read the chapter in light of this analysis was that it addresses a significant aspect of networks that Castells does not — namely, a rhizomatic approach to networks problematizes the very definition of GA I established during my Re/Proposal. In short, applying Castells profited from the boundaries I placed on the OoS; applying Deleuze & Guattari requires eliminating the boundaries, preferring instead a situated, chronological cross-section as a set of boundaries enabling analysis.

Second, a note about this cross-sectional approach. In my scaffolding outline, I referred to a “flattened, rhizomatic” approach to composing and networks. Placing these two concepts together elicited useful feedback and discussion during the following class, as a result of which I realized that rhizomes are not naturally flattened. While Deleuze & Guattari (1980/1987) refer to flattened multiplicities, they do so in the context of many dimensions: “All multiplicities are flat, in the sense that they fill or occupy all of their dimensions” (p. 9). In fact, rhizomes are unpredictably dimensional; connections can and must occur along all dimensions: “any point of a rhizome can be connected to anything other, and must be” (p. 7). Since the boundaries of such a “network” can’t really be established, one way to analyze the rhizome is to take a cross-sectional slice, situated in space and time, of the rhizome and examine the relationships among points in the rhizome in this “flattened” slice. The rhizome is a multidimensional assemblage, not a flattened network.

These two notes represent realizations that complicate and problematize the restrictive perspective I offered of GA as a network. Limiting the network to GA activities and data model resulted in limits to what I could discuss in my application of Castells. For example, in discussing the birth and death of the network, I cut short my analysis with this limiter: “While many other actions by agents outside the GA network may affect the growth or dissolution of the network, they are outside the boundaries of the GA activity and data model.” Similarly, when addressing nodal situation and relations, I wrote this limiting statement: “Beyond the boundaries of the OoS, of course, Google serves plenty of data, in the form of ads, back to users. But that’s now beyond the scope of this study.” These limits were real — the boundaries I established for describing GA as a network did, in fact, prevent addressing aspects of the network — but they do not reflect an accurate mapping of GA network activity. Deleuze & Guattari (1980/1987) point out that “the rhizome is altogether different, a map and not a tracing” (p. 12, emphasis original). Tracing is the role of centralized control, of perspectives limited by binaries and “tree logic”: “What distinguishes the map from the tracing is that it is entirely oriented toward an experimentation in contact with the real” (p. 12). A mapped understanding of GA must address its real complexity, its nodes and connections in terms of real experiences, not centrally-defined boundaries.

A mapped, cross-sectional perspective on GA as a network was, to my surprise, the goal of my first case study. In fact, the first visualization of the network I provided was a portion of a Popplet titled “Visualizing a Partial Google Analytics Data Set.”

Screen Shot 2014-05-06 at 8.03.11 PM

Figure 1: Visualizing a sample Google Analytics data set from Case Study #1Popplet

My original attempt to visualize and define GA as a network was more chaotically rhizomatic than any other depiction I’ve attempted since. In fact, for much of the rest of the semester, I’ve been struggling to trace my understanding of GA as a network, when in fact Deleuze & Guattari would have me do precisely the opposite: map the multiplicity of GA as assemblage, depicted as a cross-sectional portion of the network situated in time and space.

Mapping GA as rhizome means accepting that users, servers, computers, mobile devices, browsers, operating systems, marketers, developers, programmers, designers, GA account administrators, Google data centers, Google programmers and server maintenance personnel, homes, home offices, office buildings, network cables, routers, switches, weather conditions, satellites, trans-Atlantic communications cables, seawater, signal degradation, electrons, light energy, insulators, and theorists must be included as nodes in the GA rhizome. GA collects data on some of these dimensions; other dimensions, however, are embedded as affordances and constraints to the web technologies that enable GA to measure dimensions at all, so these affordances and constraints must also be depicted in a cross-section of GA as rhizome.

There’s a reason Deleuze & Guattari did not include a visualization of the rhizome on their chapter. It’s too complex, too multi-dimensional, to capture in a 2-dimension drawing. But I’m going to give it a shot.

Popplet mind map

Figure 2: Visualizing Google Analytics as a Rhizome—Popplet

Figure 2 depicts a rhizome cross-section of a single node, User, and the connections that exist among dimensions of the GA data model, website affordances and constraints, website creators, and Google personnel. What this depicts is that a User connects from and to most of the nodes, that the nodes connected to the User are connected to one another, and that relationships proliferate exponentially if extrapolated to the entire list of dimensions. And these dimensions are themselves necessarily limited (perhaps even cross-sectioned) by the visualization technology and my own time and patience. Were I to connect all of the non-technological aspects to the User—like location and weather conditions — the rhizome could go on forever. The point is that mapping the actual rhizome, rather than tracing the limits of the network, generates the rhizome itself. Or, as Deleuze & Guattari (1980/1987) propose, “The map does not reproduce an unconscious closed in upon itself; it constructs the unconscious. It fosters connections between fields, the removal of blockages on bodies without organs, the maximum opening of bodies without organs onto a place of consistency. It is itself a part of the rhizome” (p. 12).

Closing Gaps

Castells offers a remarkably cogent and highly matched means of analyzing GA as a network as defined by Google itself: in terms of GA activities and the GA data model. Castells addresses issues of localization and globalization in ways that make sense for GA defined as Google defines it. Here’s my conclusion from Case Study #2.

While Castells addresses the local, he tends to discuss localization in terms of groups rather than individuals. In this way, Castells more closely resembles ecological theories that apply to organism categories rather than to individual organisms. He regularly refers to groups of people and nodes: the managerial elites (rather than individual leaders), the technological revolution (rather than revolutionary technology pioneers), and the global and local economy (rather than the economic wellbeing of the individual small business owner). The result is that I can’t really address the individual user as a single agent in GA. Then again, this is hardly a hardship, in that GA aggregates data and anonymizes identities. GA, too, resembles an ecological theory rather than a rhetorical theory; it focuses on profiles of territorially localized users rather than individual users in a specific city. As a result, Castells and GA match rather nicely in defining the boundaries of the discussion. In fact, I’d argue that GA (and Google more broadly) represent precisely the network society Castells defined in his text. It’s interesting that he didn’t predict or recognize the rise of Google as I would have expected him to do in his 2010 preface. And Castells’ (2010) discussion of communication media clearly did not predict the popularity or ubiquity of Google’s YouTube on the network as a differentiated medium whose content is driven by user tastes and users-as-producers (p. 399).

Once we admit the possibility that GA is not just what Google says it is, but that GA represents a much wider and broader rhizome of connections, Castells no longer adequately describes the network. GA as rhizome requires additional theoretical application for understanding and visualizing.

Frankentheory

After a semester of theorizing, what’s my own theory of networks?

Rhizome illustration

What I think a rhizome looks like. “The Opte Project” by Barrett Lyon. Creative Commons licence CC BY-NC-SA. From The Accidental Technologist‘s post The Way of the Rhizome #h817open

Networks are local. They are also global. This is not dualism, but convergence. Local and global converge in time and space, and we must be prepared to engage in both simultaneously. The global remains rooted in the local; local conditions and environments affect and influence connections to the global. In our efforts to understand global network activity, we should not lose sight of the affordances and constraints of local conditions, including available access to the internet, proximity to other nodes, and the politics of nodal connectivity.

Networks enable nodes. A collection of nodes does not a network make. Networks enable nodal activity; this means that network frameworks must be in place for networks to exist and start collecting nods. This also means that the activity of collecting nodes in networked. The network can grow well beyond its framework in unexpected and unpredictable ways, and this should be expected, anticipated, and planned to the extent possible.

Networks are rhizomes. Or at least rhizomatic. They are unlikely to require or have inherent hierarchical structures; these will have to be applied to the network. Rhizomatic structure and growth suggest unpredictability of nodal connections. As I understand rhizomes, the importance of any node being able to connect to any other node — or to anything, for that matter — cannot be overstated. It is this aspect of rhizomatic connectivity that I would consider “flat.” There are neither more nor less important nodes; there are no inherent political relationships between and among nodes. Any political power attributed to the node will either be self-contained or bestowed from outside the rhizome; within the ecology of the rhizome, all nodes are equally capable of connecting to all other nodes and to anything outside the rhizome. In this sense, I would suggest that rhizomes are politically flat.

Networks can be analyzed in cross-section; they are very difficult to analyze in real time as they exist. They are both too large to examine as a whole and too complex to analyze as active connections are “firing.” Cross-sections can be taken of specific aspects of the network or of the network as a whole. Cross-sections are frozen in time and show little activity, merely traces that can be followed and explored. Networks contains a multiplicity of simultaneous connective activity; our abilities to analyze simultaneity is limited. Instead, we must follow specific threads of connectivity through time and space to analyze them. Such analysis is made possible through cross section.

Google Analytics’ Contributions to English Studies

First, GA can and should be critically examined as a rhetorical technology. GA activity includes reporting. These reports are discursive and rely on visual and written rhetoric to communicate meaning. The “meaning” of a GA report can be manipulated like any other statistical data. Its meanings depend on local environment and conditions, comfort with standard and local meanings of GA terminology (like “session” or “user,” for example), and familiarity with the GA data collection model. Its visualizations can be analyzed for clarity and transparency, for cultural or sociological bias (related to colors used, default views, and other determined factors), and for its connectedness to other discursive elements (like websites whose visitor traffic it measures). Critical rhetorical analysis of GA reports could easily be an object of study by itself.

Second, GA can and should be critically approached as a black-boxed network whose data manipulation and configuration are largely hidden, lacking transparency. Google’s business model depends on its proprietary search results algorithms. It protects that algorithm carefully; while GA reporting is not directly dependent on the search algorithm, website visit data contribute to search results. Full disclosure of its data configuration and processing activities would likely reveal much about Google’s search algorithm; as a result, these processes are only partially disclosed. Google’s own Analytics help files and tutorials explain the order, purpose, and general procedures of data configuration and processing, but these files and tutorials do not reveal in-depth specifics on how collected data are processed into aggregate tables, nor how those tables are then indexed for rapid, near-instant on-the-fly reporting. Google’s market share in web search and advertising result in the formation of what Althusser (1971) called a repressive state apparatus; I suggest that GA is an ideological expression of that apparatus, or an ideological state apparatus. While neither Google nor GA is a state in a political sense, its size and clout suggest an industrial state-like entity with resources and influence strong enough to manipulate or evoke responses from other political entities, as it has done recently in relations with the government of Russia (Khrennikov & Ustinova, 2014).

Third, GA results themselves can and should be critically examined. Far too many otherwise critically-written journal articles use GA results as instrumental rather than mediated. That is, GA report data are accepted as unqualified and accurate reflections of website traffic rather than mediated reports of visitor activity. Little care is given to providing GA-specific definitions of terminology like “session” and “user.” This acceptance can result in significant reporting issues — I’m experiencing a particular situation as I type in which Google has revised a reporting criterion from “visits” to “sessions.” While these two terms are being used synonymously, one implication is that GA has removed the dimension of “unique visit” from its reporting matrix. GA’s definition of session doesn’t differentiate between unique or repeat visits among sessions, as each session is considered a unique event regardless of the identity (which may not be accurately known) of the visitor. Several reports I provide my dean and marketing director were based on unique visit numbers; as a result, I’m forced to rework all of my reports to reflect sessions rather than unique visits. This has implications for perceptions of “progress” and “improvement” among senior leadership, a particularly uncomfortable reality brought to bear this week. (Google changed its reporting structure without fanfare on April 16, announced in a Google+ post.)

Finally, GA’s data collection method can and should be understood as discursive. Individual GIF calls that report data back to Google servers do so in text tags attached to tracking pixels generated through data collection. For example, every GA tag begins with “utm,” a prefix whose meaning is unclear. Many data points are collected in abbreviations whose symbolic meanings would be interesting to explore. Again, GA offers few clues for more obscure abbreviations, although Google does provide a list of many (but not all) dimensions collected via tracking pixel calls. Some of these symbols are explained in the Google Developers (2014) Tracking Code Overview. While parameter abbreviations are obscure, the values themselves are even less clear. Consider the parameter/value pair “utmul=pt-br”: the utmul parameter represents “browser language” while the pt-br value represents “Brazilian Portuguese.” This symbolic communication system is itself fodder for rhetorical analysis and interpretation.

References

Althusser, L. (1971). Ideology and ideological state apparatuses (Notes towards an investigation). In B. Brewster (transl.) & A. Blunden (trans.), Louis Althusser archive. Retrieved from https://www.marxists.org/reference/archive/althusser/1970/ideology.htm (Original work published in Lenin philosophy and other essays)

Castells, M. (2010). The rise of the network society [2nd edition with a new preface]. Chichester, UK: Wiley-Blackwell.

Deleuze, G., & Guattari, F. (1987). A thousand plateaus: Capitalism and schizophrenia. (B. Massumi, Trans.) Minneapolis, MN: University of Minnesota Press. (Original work published 1980)

Google. (n.d.). Algorithms. Inside Search. Retrieved from 1 May 2014 from https://www.google.com/insidesearch/howsearchworks/algorithms.html

Google. (2014). Dimensions and metrics. Google Analytics Help. Retrieved from https://support.google.com/analytics/answer/1033861?hl=en

Google Analytics. (2014, April 16). Understanding user behavior in a multi-device world (Web post). Google+. Retrieved 1 May 2014 from https://plus.google.com/+GoogleAnalytics/posts/LCLgkyCn4Zi

Google Developers. (2014, April 16). Tracking code overview. Google Developers. Retrieved from https://developers.google.com/analytics/resources/concepts/gaConceptsTrackingOverview#gifParameters

Krennikov, I., & Ustinova, A. (2014, May 1). Putin’s next invasion? The Russian web. Bloomberg Businessweek. Retrieved from http://www.businessweek.com/articles/2014-05-01/russia-moves-toward-china-style-internet-censorship

[ Feature image: Today's latte, Google Analytics. CC licensed image from Flickr user Yuko Honda ]

Final Reading Notes: Rickert, Ambient Rhetoric, Hip Hop

I have had several discussions about ambience over the years. The reason being that before I came to English Studies, music was my life. We often discussed ambience in regards to which space would produce the best sound. It is easy for a violin to be drowned out without the right atmosphere. We used to […]

Coda: Rickert’s Wonderful World of Oz Meets Pocahontas

First, an aside: I couldn’t stop myself from thinking of this scene from The Wizard of Oz in an entirely new way. While it’s clearly made with the human worldview of home in mind, I began to think of the … Continue reading

Mindmap Doused with Network Societies

Mindmap: http://popplet.com/app/#/1589875

Mindmap updated_April 13

Mindmap updated_April 13

So it begins. Rise of the Network Society Theory by Manuel Castells, and it all wraps up into the mindmap. How to connect a theory that is so vast, encompassing economics, technology, culture, societal growth, metropolitan regions, global relations, historical pathways? Castells’ theory, at least what I read in volume 1 (the other two volumes were not assigned), had a lot of traces of Actor-Network Theory, Ecology Theory, Hardware/Software Theory, and Genre Tracing Theory. There were probably others, especially since Foucault is that which is always found to be underlying theoretical works we have read since our introduction to him, but these four theories made the most sense for me to connect to Network Societies for the frame of my mindmap.

Now that we have the overarching (though consciously limited) connections out of the way between Castells’ mega-theory and previously dealt with theories, let’s see what nodes I’ve made.

First node: “The most important characteristic of this accelerated process of global urbanization is that we are seeing the emergence of a new spatial form that I call the metropolitan region, to indicate that it is metropolitan though it is not a metropolitan area, because usually there are several metropolitan areas included in this spatial unit. The metropolitan region arises from two intertwined processes: extended decentralization from big cities to adjacent areas and interconnection of pre-existing towns whose territories become integrated by new communication capabilities…It is a new form because it includes in the same spatial unit both urbanized areas and agricultural land, open space and highly dense residential areas: there are multiple cities in a discontinuous countryside. It is a multicentered metropolis that does not correspond to the traditional separation between central cities and their suburbs…Sometimes, as in the European metropolitan regions, but also in California or New York/New Jersey, these centers are pre-existing cities incorporated in the metropolitan region by fast railway and motorway transportation networks, supplemented with advanced telecommunication networks and computer networks. Sometimes the central city is still the urban core, as in London, Paris, or Barcelona. But often there are no clearly dominant urban centers” (Castells xxxiii). I linked this quote with one from Latour regarding “the question of the social,” with social actors defining and redefining the movements. Networks of people, businesses, cultures, and social groups, along with the objects and technologies they employ to function, are the actors in ANT, but the groups within which they move and act and trace are part of a lager network that is part of an even larger network, with the layers extending out into the global society.

Second node: “the network enterprise makes the material the culture of the informational, global economy: it transforms signals into commodities by processing knowledge” (Castells 188). I chose this quote because it reminds me of the ways that Cloud Computer, hardware/software, Foucault’s archives, Latour’s conversations about technology and objects are helping to transform what are the material goods of our globally interlaced, informational economy. Goods are still being sold, but information tends to have a higher price.

Final node: “the shift from industrialism to informationalism is not the historical equivalent of the transition from agricultural to industrial economics, and cannot be equated to the emergence of the service economy. There are informational agriculture, informational manufacturing, and informational service activities that produce and distribute on the basis of information and knowledge embodied in the work process by the increasing power of information technologies. What has changed is not the kind of activities humankind is engaged in, but its technological ability to use as a direct productive force what distinguishes our species as a biological oddity: its superior capacity to process symbols…The informational economy is global. A global economy is an historically new reality, distinct from a world economy…A global economy is something different: it is an economy with the capacity to work as a unit in real time, or chosen time, on a planetary scale” (Castells 101). I linked this quote with Foucault’s concepts of “History of Ideas” and the dangers to the historian being too complacent by that which has been written in history books. I made the strongest connection here and chose this quote specifically because it was a new way of seeing how different societal economies do not just end. Instead, they continue folding back into the newer movements going on. Agriculture never ends because people always need food. Industry never ends because people want (and, usually, need) things. History is not linear, even within movements towards societal restructurings. It also showed that the network of society is founded on many things, and different types of economies create the foundation upon which people work and live, even when certain types are maginalized, pushed out of view except to be viewed with nostalgia (reminds me of the truck commercials with farmers).

It’s Another Day, Another Week


Case Study 3 — MOOCs and Student Learning: Under the Microscope

The rhetorical nature of classroom spaces has certainly influenced our field’s scholarship when exploring digitally mediated writing classrooms. Terms such as constructed, architecture, location, ecology, environment, and space appear regularly in our field’s discussions of where and how writing takes … Continue reading

MindMap#11: Neurobiology

Never thought I’d be typing the words Neurobiology. This week’s mind map was the easiest one for me. As I was doing the reading, I was thinking of connections. I imagined myself drawing lines from How Stuff Works to Dendrites and Axons and then drawing connections between Buses and Action Potential and Snapchat. I did […]

Reading Notes #10: Neurons and Networks

This week’s reading on Neurobiology reminded me why I am an English Major. I have no interest in science (beyond chemistry, which helps with cooking) and lack the ability to understand “sciencey” words. “A single cubic centimeter of the human brain may contain well over 50 million nerve cells, each of which may communicate with […]

Mind Map: Ecologies Part II (March 30th)

Link: http://popplet.com/app/#/1571354 Last week’s activities asked us to apply our network questions to the Ecology readings of Syverson, Spellman, the Cary Institute, and fill in the gaps with Guattari, resulting in new connections for my mind map. And even though … Continue reading

Re/Proposed Object of Study: Google Analytics

I’m sticking with Google Analytics as my object of study. I’m too invested in the object, and it remains an important part of my professional responsibilities and therefore an object that I need to study, whether for this class or for professional development. In fact, this month I earned another certificate of completion for a Google Analytics Academy program, “Google Analytics Platform Principles.” The outcomes benefit me academically and professionally: the course contributed to my understanding of the underlying data structure and collection principles for the assignment’s ongoing case study, and it provided me some intriguing ideas for importing data into GA beyond those data collected by the tracking code to help my team measure our marketing effort success.

The GA platform consists of four activities based on dimensions (user characteristics) and metrics (quantitative interaction information): collecting, configuration, processing, and reporting. The Google Developers guide provides the following helpful visualization to describe the platform’s activity.

Google Analytics Platform Components visualization

Google Analytics Platform Components. Original image on the Google Developers Guide.

Collection: User-interaction data are collected through either the embedded code snippet or through the measurement protocol, an alternative system for manually submitting user-interaction data from mobile apps and other internet-connected appliances.

Configuration: Data are configured by the GA account manager(s) through the GA web interface or management API. Configuration settings permanently delimit data collections; as a result, at least one configuration is required to be unfiltered to ensure all possible data are accessible in at least one configuration, or, as GA refers to these configurations, Views.

Processing: Based on configuration settings (filters, groupings, etc.), raw data are processed and stored in aggregated data tables and in configured raw forms. Data tables organize data in pre-determined collections for quick access, but queries can be constructed to pull data from configured raw forms. Often such queries will sample data rather than pull all values, once again to speed the presentation of results.

Reporting: Data are reported via the GA web interface or via the Core Reporting API or Multi-Channel Funnel Reporting API. Reports can be constructed that will not provide meaningful results; not all dimensions are compatible or reportable with all metrics. As a result, GA account managers must construct views carefully and develop reporting goals and practices that yield meaningful and accurate results.

The GA data model consists of three levels that help collect and organize dimensions and metrics: user (visitor), session (visit), and interaction (hit). Lesson 1.3 in the GA Academy Platform Principles course offers the following visualization of this model.

Google Analytics data model visualization

Overview of the Google Analytics data model. Original image from the GA Academy Platform Principles Lesson 1.3.

User (visitor): The user is identified by the browser or mobile device the visitor used to access the site.

Session (visit): The session is defined as the time the user (browser or device) was active on the website.

Interaction (hit): Interactions are individual actions taken by a user that sends hit data to GA servers. These may be pageviews (loading the page), events (clicking on a movie button), a transaction (checking out of an online store), or a social interaction (sharing content on a social device).

As this chart reveals, the GA data model breaks engagement into a hierarchy. Interactions occur within sessions, and sessions are associated with a user. A user may have multiple sessions, and each session may have multiple interactions and interaction types. The GA account manager must determine measurement scope using this hierarchy. Is the goal to measure and report on interaction-level activity (number of pageviews regardless of user or session); session-level activity (common entrance or exit pages for sessions regardless of user); or user-level activity (number of unique users who completed a specific task, regardless of session)? The measurement goal determines the reporting scope.

So far, I’ve struggled to define the scope of GA as I’ve applied theories to it.

I’ve described GA as the reporting “arm” of a web development and visitor ecology in which nodes include web marketers and web developers, web services technicians and coders, database managers, marketing writers, content managers, website visitors, browsers and platforms, Internet hardware and software, and GA servers. In this model, GA collects traces of the active relationships that occur among these nodes.

I’ve also described GA as a mediating technology that directly and indirectly limits and controls the data collected from website interactions. Specific, delimited data points are the target of data collection and reporting. Those data points, and only those data points, are available to GA end users who seek information about user behavior on a website.

Defining Google Analytics

While neither of these descriptions is inaccurate, neither quite achieves the focus I’d like to apply to my case studies. I propose a description that focuses more directly on the GA platform’s four activities and the GA data model. Specifically, GA is a digital tool that collects user interaction data at three levels — user, session, and interaction — in the form of dimensions and metrics. Data collected are configured based on specific, targeted, goal-oriented decisions by GA administrative users, processed in accordance with those decisions, and output through aggregated data tables to GA users, both administrative and standard or limited-access users. This description focuses specifically on agency of GA administrators; in the case of my GA account for the University of Richmond School of Professional and Continuing Studies, that agency resides primarily in me and indirectly in our marketing team.

Application to English Studies

GA focuses on assessing outcomes. GA administrators configure data collected in GA to assess the results of specific marketing efforts. For example, in order to examine general and specific browsing patterns of external (non-UR) visitors, I need to configure our GA account with a view that filters out internal (UR-based) web traffic by IP address. Examining these browsing patterns enables our marketing team to determine whether the information we’re providing is attracting prospective students in ways that our strategic marketing plan requires or expects. In short, we are using configured data reports to assess the extent of success of our web-based marketing efforts. Such assessments offer English studies models for assessment that can and should be incorporated into writing assessment, writing program assessment, perhaps even departmental assessments. Data-driven assessments can and should include both user characteristics and metrics; that is, they should be based on user profiles intentionally constructed to include or reflect contemporary, lived experience. For English studies, this means our data collection efforts must be based in localized environments and configured to process and report on specific objectives and outcomes.

GA collects metrics, but its ability to collect dimensions (user characteristics) means that its reporting is verbal and numerical. As such, its reports are rhetorical. They can and should be problematized as rhetoric. Specific decisions to collect or not collect demographic data, for example, could be problematized using cultural studies or gender studies. Specific ways of reporting demographic data, including terms used to describe or define those demographic qualities, are also areas to be analyzed and problematized. From its use of colors to its data processing strategies (which remain obscure), GA is fair game for rhetorical analysis and critique, and scholars in English studies should focus more critical attention on analyzing GA rather than using GA to measure the success of web-based instructional or informational efforts.

GA as Network

GA is free and remarkably powerful. Google appears to be working to make it even more broadly applicable as a digital analytics platform, not simply a web analytics platform. The distinction is important to its role as a network. Web analytics are useful and meaningful, but they are limited in scope to websites and web interactions. Digital analytics, on the other hand, encompass a much broader category of data, like digital advertising (including web-based and localized advertising efforts, like digital billboards and online display ads), appliance function (including communications between digital devices like wifi-connected refrigerators or cell-connected washer/dryer sets), and mobile phone uses beyond calling. As GA broadens its applicability as a digital analytics platform, its reach and scope become global, both in location and function. GA can begin to measure global network functions; its ability to measure those functions is dependent on its own flexible network structure. Its collection, configuration, processing, and reporting functions are network-based and network-focused. Its internal structure, to the extent Google allows us to view it, is based on related aggregated data tables. And its objects of measurement are related digital nodes on networks. The result is that GA is both network reporter and networked reporter.

[Top image: Screen capture of Google Analytics homepage: google.com/analytics]

Mind Map #10: Seeking Homeostasis

Popplet mindmap visualization

Mindmap #10: Seeking Homeostasis (Popplet visualization)

The ecology of my mind map seeks homeostasis, a natural balance among its many theories. My mind map has become, in Charles Darwin’s words, a “web of complex relations” (cited in Spellman, 2007, p. 4).  Well, maybe not as complex as all of nature, but if we follow the formula for the value of a network from Castells (2000) — “the value of a network increases as the square if the number of nodes in the net” (p. 71), expressed as V=n(n-1), where n is the number of nodes in the network — then we’re looking at a pretty significant number of potential connectivities among all these theories. That’s pretty complex. (I had to check: the number of nodes related specifically to theories in the mind map is around 75 right now, so V=7574. That’s higher than any calculator I have access to can count.)

I linked the three ecologies from Guattari to my ecology node. I used Spellman’s (2007) focus on homeostasis (p.15) as a node as well, connecting it to the both the relationship between the organism and the environment (an important aspect of the definition of ecology) and the relationship between Guatarri’s three ecologies. Both Spellman and Guattari invoke the importance of seeking an equilibrium within ecologies or biosphere. Since “it is people through their complex activities who tend to disrupt natural controls” (Spellman 2007, p. 15), achieving homeostasis in ecosystems in which humans are active participants is incredibly difficult.

I focused specifically on the relationship between environment and organism as the focus of homeostasis, but I also added distributed intelligence as a node related to all aspects of the network of ecology. Distributed intelligence, cognition, value — whatever the term we wish to use — is becoming an important, common theme among several theorists. Our theorists are no longer willing to propose meaning be found in a single aspect of a networked environment; on the contrary, value has been placed in the interrelationships among network nodes. If I had to define what I consider a network right now, I’d probably focus on distributed value among actively connected nodes. Individual nodes may be valuable, but in the network system, the value of an individual node is found in its contributions to the distributed meaning or value of the network itself. And that distributed meaning gains value only in its active state; in a passive state in which connections are theorized but not activated, the nodes provide only a framework for potential connectivity, distribution, and meaning or value.

I’m not sure how to convey all this in a mind map yet, but I expect I may center and enlarge “Distributed Intelligence” and start connecting many different mind map nodes to that important concept as I move forward. Castells shows so signs of moving away from this model of distributed meaning and value. And maybe it’s in emphasizing this distribution that my mind map will find the homeostatic condition it seeks (or maybe I’m on the one seeking it).

References

Guattari, F. (2012/1989). The three ecologies. Trans. Ian Pindar & Paul Sutton. London, UK: Continuum International Publishing Group.

Spellman, F. R. (2007). Ecology for nonecologists. Lanham, MD: Government Institutes, 3-23; 61-84.

[Top image – Narrative Ecology Framework flashcards: CC licensed image from Flickr user Crystal Campbell]

Mind Map #10: Seeking Homeostasis

Popplet mindmap visualization

Mindmap #10: Seeking Homeostasis (Popplet visualization)

The ecology of my mind map seeks homeostasis, a natural balance among its many theories. My mind map has become, in Charles Darwin’s words, a “web of complex relations” (cited in Spellman, 2007, p. 4).  Well, maybe not as complex as all of nature, but if we follow the formula for the value of a network from Castells (2000) — “the value of a network increases as the square if the number of nodes in the net” (p. 71), expressed as V=n(n-1), where n is the number of nodes in the network — then we’re looking at a pretty significant number of potential connectivities among all these theories. That’s pretty complex. (I had to check: the number of nodes related specifically to theories in the mind map is around 75 right now, so V=7574. That’s higher than any calculator I have access to can count.)

I linked the three ecologies from Guattari to my ecology node. I used Spellman’s (2007) focus on homeostasis (p.15) as a node as well, connecting it to the both the relationship between the organism and the environment (an important aspect of the definition of ecology) and the relationship between Guatarri’s three ecologies. Both Spellman and Guattari invoke the importance of seeking an equilibrium within ecologies or biosphere. Since “it is people through their complex activities who tend to disrupt natural controls” (Spellman 2007, p. 15), achieving homeostasis in ecosystems in which humans are active participants is incredibly difficult.

I focused specifically on the relationship between environment and organism as the focus of homeostasis, but I also added distributed intelligence as a node related to all aspects of the network of ecology. Distributed intelligence, cognition, value — whatever the term we wish to use — is becoming an important, common theme among several theorists. Our theorists are no longer willing to propose meaning be found in a single aspect of a networked environment; on the contrary, value has been placed in the interrelationships among network nodes. If I had to define what I consider a network right now, I’d probably focus on distributed value among actively connected nodes. Individual nodes may be valuable, but in the network system, the value of an individual node is found in its contributions to the distributed meaning or value of the network itself. And that distributed meaning gains value only in its active state; in a passive state in which connections are theorized but not activated, the nodes provide only a framework for potential connectivity, distribution, and meaning or value.

I’m not sure how to convey all this in a mind map yet, but I expect I may center and enlarge “Distributed Intelligence” and start connecting many different mind map nodes to that important concept as I move forward. Castells shows so signs of moving away from this model of distributed meaning and value. And maybe it’s in emphasizing this distribution that my mind map will find the homeostatic condition it seeks (or maybe I’m on the one seeking it).

References

Guattari, F. (2012/1989). The three ecologies. Trans. Ian Pindar & Paul Sutton. London, UK: Continuum International Publishing Group.

Spellman, F. R. (2007). Ecology for nonecologists. Lanham, MD: Government Institutes, 3-23; 61-84.

[Top image – Narrative Ecology Framework flashcards: CC licensed image from Flickr user Crystal Campbell]

Revisiting the Proposal: March 30

Donna Haraway has been credited as one of the first to use the term “cyborg” to describe our relationship with the Digital, as we become “hybrids of machine and organism” (151). The field of English Studies, and in particular Composition … Continue reading

Ecology of the Theories of Networks Course

Welcome to the Ecosystem of Theories of Networks!

I know it may sound a little odd to call a course an ecosystem, let alone applying ecology theory to it. But, it is an ecosystem, and for me, it an ecosystem that is part-physical classroom, part-virtual existence, and part-home environment. Most of the residents of my ecosystem show themselves in messages on Facebook, as talking-moving squares on a screen on the classroom television, and as data spilling out onto Google docs. Once a week, three others share the same physical space I do, but always for a (roughly) two hour period of time. But, you ask, can this even remotely be classified as an ecosystem? Well, I turn my attention to Bateson’s Ecology of the Mind, especially with the concept of the cybernetic epistemology and the “larger Mind.” With the way technology has become such a part of our lives, our environments are both physical and virtual, and should not be separated. Welcome to the future.

 

Larger Mind? Mind as Computer? Image hosted on the website Advanced Apes.

Larger Mind? Mind as Computer? Image hosted on the website Advanced Apes.

As Gibson points out, in his chapter “The Theory of Affordances,” humans have modified our environments “to change what it affords [us]. [We have] made more available what benefits [us] and less pressing what injures [us]” (130). Gibson tells us that, “The affordances of the environment are what it offers the animal, what it provides or furnishes, either for good or ill” (127). So what affordances are now offered to me in this hybrid ecosystem of my course? What can be afforded within a virtual environment? Many things, actually.

Take, for our first example, this blog. What does this digital space provide for me? I am the organism and this is my environment. While it does not allow me to modify everything in my space (especially as I am lacking in things like HTML know-how), but it does allow me to draw in images, videos, and text so as to express my ideas, creating a space for me. The blog then becomes my place, with the class shared folder and Facebook back channel as my habitat, from which I can interact with the other residents of my ecosystem and neighboring ecosystems. The class website is another space within the ecosystem that offers me affordances (making me accountable for the work I do) as it becomes the center of which all of my work and that of my peers revolve around. The schedule affords me deadlines and the ability to time-keep based on assignments, provides me links to external readings and reminds me of what I need to read, allows me to add quotes to the discourse of the class, and further my understanding of the coursework with the sporadic inclusion of videos throughout the schedule.

But which learning space allows for me to lay out my ideas, made connections, without feeling like I have to explain those connections as I make them? Ah, the mindmap is the part of the ecosystem (as all of our mindmaps are accessible through our blogs, which are then accessible through the course website), but the affordances of Popplet is very limited compared to that of the blog and the website. Through the software, I am afforded the creation of nodes that can be filled with text and visual objects, as well as creating multiple connections between those nodes. However, the affordances of this particular environment are limited by the capabilities of the code that underlies its structures. Once the mindmap becomes too large, it is impossible to see the entirety of the mindmap without the words  becoming blurry, but the software allows for differentiating among thoughts by having nodes color-coded (though the color choices are limited). The larger affordance of Popplet is that I can share my work, deciding whether I want to make it private, public but only to those with the link, or public to the whole of the Popplet ecosystem. I can stay in my semi-hiding place or I can be out in the midst of my habitat.

Now, the last technology/application I am going to touch on in my ecosystem, with the distributed consciousness of the other residents of my Theories of Networks ecosystem kept in mind, is that of the Google docs, where we can work alone (isolation for personal projects) or come together to work simultaneously in a shared virtual space. We may not physically share the same space, but out minds, through code, can occupy and mingle together. The affordances of this space come through in the ability to modify the visual appearance of the text, and to link among parts of the document, out to other documents, websites, images, and videos. It affords multiple organisms in the environment to work together without on a single document, presentation, drawing, and still be able to talk through chat. Google docs then affords me to save the work I have done, or export it out, as well as import in documents created outside of Google doc, allowing it all to exist within the Google Drive ecosystem in which part of the Theories of Networks ecosystem thrives, but only part. This collective consciousness I share with my peers always exists within several ecosystems that are already in play, and we can carve our own space out of the worlds founded by code, zeroes and ones represented through user interfaces.

Where to go from here: Terminator, BBC style?

What happens when technology goes too far? Nah, that'll never happen. Image hosted on Photobombs section of Likes.

What happens when technology goes too far? Nah, that’ll never happen. Image hosted on Photobombs section of Likes.

To the Victor Goes the Spoils:


Reading Notes: Ecology & Affordance

Bateson

Bateson, G. (1987/1972). Steps to an ecology of mind: Collected essays in anthropology, psychiatry, evolution, and epistemology. Northvale, NJ: Jason Aronson, Inc.

To separate the individual from the society, or the individual mind or thought from the global mind or thought, is to deny the ecological unity of creatura, of the creative self. Individuals are part of ecologies; to reduce oneself to a single ego is to deny the relationship of the individual in the larger social.

I found most interesting that ecology might be considered a way in which ideas — differences that make a difference — are transformed and remain alive beyond the individual mind. The mind is not simply an internal space. It’s an ecology that connects beyond the self, beyond the individual, to encompass history and society. Since “in the world of mind, nothing — that which is not — can be a cause” (p. ???), ecology theory suggests that binaries and dualities, like cause and effect, offer only an incomplete picture of reality. Reality consists of causes and effects, but it also consists of invisible connections made in the world of mind, connections that cannot be empirically proven as “existing” in the physical sense.

Bateson puts this another way in his “Comment on Part V”: “In sum, what has been said amounts to this: that in addition to (and always in conformity with) the familiar physical determinism which characterizes our universe, there is a mental determinism” (p. 472). The key is immanence versus transcendence. Transcendence leads to divine or transcendent agency, while immanence yields communal and networked agency within systems. And it’s this sense of networked agency that relates most directly to our understanding of network theory.

Gibson

Gibson, J. J. (1986). The ecological approach to visual perception. Hillsdale, NJ: Lawrence Erlbaum Associates.

There’s clearly confusion over the meaning of “affordance,” as demonstrated in this visualization headlining a blog post titled The affordances of objects and pictures of those objects on the blog Notes from Two Scientific Psychologists.

“Affordance” is defined as that which is provided or furnished, either for good or for ill. Affordances must be determined relative to the subject, not “objectively.” As a result, affordance may be a way to subvert the objective/subjective divide. Since determining affordances requires referencing the observer, a theory of affordances enables us to examine the relationships among objects and subjects in an ecology that denies dualism in favor of ecology. In short, affordances are about networks; the relationship among objects and subjects in an ecology is that of networked connections that connect nodes.

Affordance theory does not accept as valid either mind-matter or mind-body dichotomies. Instead, it recognizes the ecological connections that can’t be ignored or explained away. Like ANT, affordance theory seeks to examine connections among subjects and objects in all their complexity. In addition, a theory of affordances does not require the perceiver to “assume fixed classes of objects.” Like Foucault and ANT, affordance theory resists placing subjects and objects into fixed classifications. “The perceiving of an affordance is not a process of perceiving a value-free physical object to which meaning is somehow added in a way that no one has been able to agree upon; it is a process of perceiving a value-rich ecological object.” The affordance is perceived as ecological in nature, lacking singular or classified focus.

Norman

Norman, D. (n.d.). Affordances and design. Don Norman Designs. Retrieved from http://www.jnd.org/dn.mss/affordances_and_desi.html.

Perceived affordances differ from real affordances in that perceived affordances focus on the user’s perception that a meaningful action is possible. Norman writes, “I introduced the term affordance to design in my book, ‘The Psychology of Everyday Things’…. The concept has caught on, but not always with true understanding. Part of the blame lies with me: I should have used the term ‘perceived affordance,’ for in design, we care much more about what the user perceives than what is actually true. What the designer cares about is whether the user perceives that some action is possible (or in the case of perceived non-affordances, not possible).” Perceived affordance focuses on what the user believes possible through the affordance. The actual affordance may not be relevant; the perception of affordance is much more important.

Norman differentiates between affordances and conventions. Cultural conventions are the way things are done in cultural contexts. The example offered is of scrollbars on a screen. They always work in a specific way that is culturally constructed and conventional. To go against this cultural convention is counterproductive.

Thoughts on Application

Visualization of cloud of icons

The world of mind: An ecology of web design. Visualizing the ecology of affordances and cultural conventions in web design. From KaJ Labs, a web design company.

Norman’s recommendations about designing for screen interfaces were right on target, although they also discouraged me a little in realizing how much cultural conventions affect pedagogical decisions. We often try to make changes to rapidly or two radically; in doing so, we push too hard against cultural conventions that make effective work possible. Norman’s concern about metaphor is more valid than I wish to admit; I’ve had a couple of experiences this semester trying to use metaphor to explain some pedagogical design decisions that backfired because students took the metaphor too literally and misunderstood assignments.

When it comes to web design, perceived affordances and cultural conventions work together with subjects to enable activity. Cultural conventions work as frameworks into which perceived affordances may be constructed that allow subjects to accomplish meaningful activity. We create web pages within conventional frameworks of programming languages, software, and hardware; we create those web pages with perceived affordances that enable users to accomplish tasks of browsing and finding information being sought. Our designs enter the ecology of all those perceived affordances constructed within cultural conventions — websites, blogs, multimodal projects, streaming audio and video platforms, and more.

[Feature Image: Ecology of the Mohave Desert. CC licensed image by Flickr user PNNL - Pacific Northwest National Laboratory]