Audience is a Way to Think

It’s a well-established truth that the easiest way to get attention is to get in the way. Crashing the seamless background against which our lives play out will do it. If you’re lucky, you get incorporated into the foreground for a little while. Otherwise, you’re a problem; you’ll get fixed  and the reaffixed.

Now, writing is a great vehicle for getting in the way. We have more ways now for anyone to send text in the direction of hypothetical eyeballs than at perhaps any other time since people first thought to exchange marks on media. But you have to understand “audience” before you can understand any one audience. When you want to move people, having a sense of their ideas, background assumptions, and expectations is oftentimes better than anything you could learn from, say, demographics.

Demographics can get you started, to be sure, but the way people group themselves is always based on ideas and expectations anyway. Better off starting there in the first place.

Hear me if you've stopped this before.

Hear me if you’ve stopped this before.

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Buffer: Save It for Later, Don’t Run Away and Let Me Down

(Being my second post in response to Jane Hart’s 10 Tools Challenge 2013)

For business, the Internet means that a potential customer could receive your message almost anywhere. But although it’s getting better at it, the Internet can’t tell you exactly how to make your message intersect with its audience at the right time, place, and condition of readiness. It’s not quite the case that f(map) = territory, but it’s close enough that one quickly finds that there needs to be a triangulation layer over it: a set of tools that, taken together, increase your potential reach and return.

This is a big issue when your business more or less lives on the Internet like Versatile PhD. We provide a variety of resources to subscribing universities that help graduate students in many disciplines explore, identify, and prepare for careers outside of the typical academic faculty path. Great stuff. But a university campus is awash in information. We’re competing with an untold number of demands on the attention of our potential users. So we’re building a triangulation layer, using two tools that were familiar to me to feed into a brand-new one. Familiar: Twitter and Google Reader. New: Buffer.

We’re a small company with a far-flung client base. We have great partners on our client campuses (career centers, graduate schools, and provosts’ offices), but we don’t have access to their communication channels. And, like us, they have to prioritize a wide range of demands and efforts, so anything we can do that calls out to their campuses will help us both.

The facts cry out for a social media solution, really. It gets at the great number of unanswered questions present at the start. How do we interact with potential users? How do we draw and then keep their attention? How do we get them to participate with us in a shared space, or even take ideas from us and propagate them in new directions? And how to do this when there’s limited time?

VPhD’s first entry into social media preceded my arrival by less than a year. My boss, the founder and CEO, went with Twitter, not Facebook. She wanted a platform for participating in conversations about the state of the PhD rather than for marketing. We’ll get to Facebook at some point in the near future – we have our hands full with the discussions and forums on the site, and don’t need another content and curation demand just now. What we did need was a vehicle to start to give the business a voice.

At first, it was the voice of my boss. Her interactions were with friends, allies, and fellow-travelers in higher education circles, primarily, with occasional forays into the career space more broadly. But when I took up the assignment, I decided that I wanted to turn that voice more overtly toward our potential users: graduate students and PhDs.

But what to tweet? There’s no shortage of articles, blog posts, and other content about the state of the PhD and higher education. All kinds of social and economic trends are relevant to the labor market in higher education.

The niche, broadly speaking is good news about PhDs and the PhD itself. Or, in hashtag form: #goodphdnews. The idea came to me in mid-December, when I’d begun exploring ways to find Tweet-able things related to PhDs or the degree itself. Important milestones in the academic calendar happen then, so it wasn’t long before I started seeing good things:

From there, it was a short mental leap to something that people in my part of DC had been doing earlier in the year – #goodWard5news – which gave me a model for the new hashtag.

It seemed like a good way to engage with potential users of our resources who might not otherwise know about us, and turn @VersatilePhD into something a little more lively than a platform from which to post relevant articles and other material. Direct connection leads to attention and communication, so we hear. So borrowing a bit of the #FollowFriday spirit, at the end of every work week, @VersatilePhD tweets out the #goodphdnews all day long. So now we have something we didn’t before: a type of story to highlight, of good things happening to or created by people with PhDs or working on them.

Over the next month or so, I started putting a few more tools in place to streamline the process. From beginning to end, it entailed a lot of work: finding the best keywords and hashtags, coding good search queries, reviewing the search results, recrafting the best ones as #goodphdnews RTs or MTs, and then finally tweeting them. After a few rounds of doing everything almost manually (and discovering that PhD tweets are a regular target of tweet-plagiarizing fake accounts), I found a way to aggregate the tweets so that I could rapidly find those with potential, and picked an automation tool for the final act of tweeting itself: Buffer.

Buffer is browser-based and straightforward. The tabbed dashboard shows the three main functions: the stack of tweets you’ve set up to go out; analytics to track clicks and engagement with those tweets once you loose them on the world; and the scheduling function, which is the heart of it all.

It runs through the browser as an extension that adds a Buffer option to any tweet viewed at (visible in the Twitter screenshots above, which I took recently) and other places. Click that link, and you get an editing window on the screen with the text of the tweet ready for quoting or editing. Share it right then, or “buffer” it for later.

Buffered tweets appear in the stack, and you can then drag and drop within the stack if you prefer a different order than the one in which you entered them. Links get rewritten with the shortener, but otherwise it works more or less transparently. Rather than assigning each buffered piece of content a time, you set up a schedule and then arrange the content over it. That seemed a little curious at first, but I’ve grown accustomed to it.

With the delivery mechanism in place, it wasn’t long before I also found a good aggregating mechanism: my dear and now soon-to-be-departed friend Google Reader. Once you realize that RSS will work on anything that can be expressed as a URL (` tweets), it’s a quick step to writing up a variety a queries that deliver an entire universe of tweets all at once.

(The sharp-eyed will notice that Buffer integrates with Reader, too.)

At this point, the #goodphdnews process is set, having just a few steps. Sign into Reader, Twitter, and Buffer. Scan the Reader stack, which shows just enough of a tweet for me to see whether it might be a good candidate. When I click through Reader into a tweet, if I want to recast it as #goodphdnews, Buffer lets me write it up instantly. It takes about an hour to scan a thousand tweets (finding the whole-cloth text of a tweet I’ve seen before indicates another fake account bot – they appear over and over again). Once I’m done, I add or subtract scheduled times for the buffered tweets to be shared. We only do this on Fridays, so the delivery happens more or less between 9am and 6pm Eastern.

Through this experience, I’ve found a number of themes and topics worth reflecting on as I continue. Social media is not a large part of my job, so finding ways to fit tools to the process makes it happen within the amount of time I can allot it. One is truly fortunate if one’s work is of a kind that presents interesting problems, and perhaps doubly so if the search for solutions actually results in something that works better and faster. Of course, it’s also true that any good problem or challenge tends to unfold into smaller problems or challenges as you work through it. In the worst case, this can lead to a sort of problem/solution cascade, where you never manage to get a good equilibrium. Wanting to connect with others in the same intellectual or business space is that kind of problem.

A complex problem will most often require multiple tools that add up to a satisfactory process or solution. Yet it also seems true that the urgency of business demands often mean that you never have the time to research a comprehensive solution, which means you’re going to end up using the tools that are closest to hand. Hopefully they’re also close enough to the desired result that they can help you triangulate toward a solution.

More to come as I continue through the 10 Tools Challenge over the rest of 2013.

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Ten Tools for 2013

Although I haven’t written about it before, I decided a few months ago to take up Jane Hart’s Ten Tools Challenge this year, after reading about it on David Kelly’s blog. This is a year when I’m learning new tools for a new job, having moved from being my own boss as a consultant and strategist to working for Versatile PhD. VPhD an internet-based business, and those prosper through one’s ability to use good tools effectively. It’s for these reasons that I’ve been thinking about this question lately: What is the nature of the connection between a tool, its purpose, and the audience for its use?

we must have a Chuck for fine work

we must have a Chuck for fine work

This was a departure from graduate school, where I had more time to experiment. Integrating technology into the classroom and the learning experience proved more complicated when I had to balance them against the basic demands of designing and delivering classes. My search for permanent academic employment took a lot of time and energy, as did other things, and so there was usually not a lot left over for experimenting with new tools.

For quite a while after it happened, leaving academia felt like losing my audience. This was much more true of my teaching than it was of my research. (The erosion of my connection to that audience had begun rather earlier; it was largely complete by the time I moved on.) The luxury of my lack of originality with tools was tied to the audience as well: in higher education, they and I were in the same place at the same time and so we could always fall back on that. But once the process of getting to what came next had started in earnest, I came to see that one answer to a loss of audience was the adoption of new tools.

You can find some of the earliest traces of this process in social media, on Twitter. It was there that I first found a cohesive group of professionals that had decided to use the platform not just as a tool for finding each other, but as a platform for sharing and developing professionally: #lrnchat. It was through that route that I heard of Jane, and learned about her work as the principal figure at the Center for Learning and Performance Technologies, or as a member of the Internet Time Alliance. And her especially relevant yearly Top 100 Tools for Learning list. The Ten Tools Challenge formalizes what many have already done: use the list as a starting point for professional development.

So I’ll be thinking of new tools as means to find new audiences and communicate with them. I’m also taking advantage of a lucky alignment: personal professional development and the development of the business of which I am part go together. I also think that changes in the tools that work for one is a way to trace development: the tool is a breadcrumb, or a chapter, or a bookmark.

My Ten Tools for 2013:

WordPress (personal; professional) Blogging more often, about a wide range of subjects.

Google Analytics (professional) Enhancing our understanding of what users do on our site.

Mailchimp (professional) Communicating updates and reminders to our promoters and champions.

Buffer (professional) Very handy for efficiently expanding the social media footprint the enterprise.

SurveyMonkey (professional) What do our users think about our site and services, now and in comparison to past surveys?

R (personal; professional, someday) One needs to be fluent with data and statistics in business more now than ever.

CodeAcademy (personal) I have a friend who is an R autodidact: she suggested I try something less complicated before R, so I’m working on Ruby.

A new RSS reader to replace Google Reader (personal) A week ago, there was something else in this slot.

Asana (professional) A project workspace the extremely distributed VPhD team uses.

Tin Can API, aka The Experience API (professional) because I’m interested in what it could be used to do to track career development or accomplishment across a distributed set of locations.

it has cost us considerable in time and money to ascertain the best Vise at the lowest cost

it has cost us considerable in time and money to ascertain the best Vise at the lowest cost

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No Mouse? No Más!

It’s difficult to know how often opportunities to change the way that an entire system of knowledge makes sense of the world really come along. By their nature, most human systems tend toward a state where reproducing the way things becomes deeply insinuated into whatever the system was intended to do. Practices turn into “the way it’s done.” Any reader can list his or her own favorite personal, professional, or historical examples, not to mention all of those within which we’re probably sitting comfortably right now.

One ready-to-hand example comes from the National section of today’s New York Times. Gina Kolata reports on a recently-published study that demonstrates some likely limitations of contemporary science’s preferred laboratory stand-in for human subjects: the mouse. It’s about the use of mice in the study of sepsis, but likely has consequences for other diseases. Short version: although mice and humans have enough in common genetically that successful tests of treatments on the one correlate with successful medical treatments on the other, where there are differences the differences really matter.

The research study here, though, had its genesis in another study by the same research team that sampled humans rather than mice. Those research questions were, for what genomic science can do today, pretty straightforward. What are the white blood cells of patients with sepsis (or trauma or severe burns) doing at the genetic level? What genes are operating, and in what combinations? By the article’s description, the researchers amassed a data set that would be the envy of anyone. But peer-reviewed publications rejected the study because the findings had not also been replicated in mouse studies.

I have to hand it to the researchers, for the next thing they did was ask themselves: What does happen in mice in situations like this? And while the article doesn’t really spend a lot of time on this part of the story, here is where I find the most interesting pivot point. They asked this question because they accepted the validity of the premise. No mouse? No más. So let’s get some mice on this.

“The group decided to look,” Kolata writes, “expecting to find some similarities. But when the data were analyzed, there were none at all.” And it unfolded from there that mice are highly resistant to the things that lead to sepsis in humans.

(At an earlier point in the article, it’s mentioned that mice are susceptible to something that resembles but is not sepsis, the implication being that the assumed similarity translated to an assumption at the level of medical understanding and clinical care.)

And so then, when the researchers turned this new finding into a paper and submitted it for review, they once again ran into the embedded assumption about mice. Rejection. Not on the basis of scientific error, but rather, as one of the lead authors characterizes reviewers’ responses, “It has to be wrong. I don’t know why it is wrong, but it has to be wrong.”

The story includes a lot of the typical features of this kind of narrative: a grounding assumption, systems of sifting and winnowing knowledge that sort on the basis of that assumption, protective gatekeepers who seem to set aside common sense in favor of what the record says should be the case. On the plus side, I see throughout one of the greatest strengths that those who do public engagement and scientific outreach can master: the value of narrowly defined claims, scope, reach, and implications. As well, it’s extremely positive that wired state of the world makes it possible for research to be widely actionable because the scope and speed of possible reception are wide and quick.

Here, the researchers were also fortunate that the grounding assumption they violated was above the surface of disciplinary knowledge where they could see it. It’s also worth noting that they could, after the first round of rejections, pivot rapidly to add a mouse component to their study. The second round of rejections is where they ventured into much more unsurfaced territory. I don’t know why it’s wrong, but it’s wrong — that kind of formation is a signal that you’re close to the heart of something very powerful. The closer you get to an unexamined but incredibly high-value assumption, the more correct you’d best come. Because it will be on.

So. No mouse: no más? Hopefully no more.

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Learned Last Week (39 of 2012)

Here are some of the ideas, observations, and insights that others shared last week, received via Twitter, Google+, RSS feed, or link round-up. Quotation implies engagement, but not necessarily endorsement.

@JAltucher, “Today You Started a Business.”

“You demonstrate credibility when you teach your employees and when you teach your customers… An important side effect of educating people is that you build presence, you build charisma, you exude confidence that is earned.”

Amy Barth (in @DiscoverMag). “Controlling Brains With a Flick of a Light Switch.”

“Deisseroth needed a miniature flashlight that could be inserted in the brain so it could travel with the mouse wherever it went.”
via @TheBrowser

@TomChatfield (in @BBC_Future), “The Decaying Web and Our Disappearing History.”

“Few things are more explicitly ephemeral than a Tweet. Yet it’s precisely this kind of ephemeral communication – a comment, a status update, sharing or disseminating a piece of media – that lies at the heart of much of modern history as it unfolds.”

@IzaKaminska (in @ftalphaville), “As the only person in the room who has apparently never written a line of computer code…

Quoting Nicholas Colas, ConvergEx group chief market strategist: “We can’t beat them on speed, so forget the first one. But can a human investor learn what these new algorithms will look for, and then base an investment style around front-running the machines? Or at least stay out of their way.”

@Quinnovator, “Transcending Experience Design.”

“There are things about experience design that instructional design largely ignores: emotion, multiple senses, extended engagement.”

@YvesSmith, “On Manichean Worldviews and Effecting Change.”

“Anyone who has studied propaganda will tell you that purveyors of that dark art work hard to eliminate nuance, and force ‘with us or against us’ choices on people when the options are almost without exception more complex.”

@PenelopeTrunk, “How to Pick a Career You’ll Like.”

“You can’t just have the life they have now. You have to have the life they lead to get there.”

@PegTyre (in @TheAtlantic), “The Writing Revolution.”

“There are phrases—specifically, for instance, for example—that help you add detail to a paragraph,” Monica explains. She reflects for a moment. “Who could have known that, unless someone taught them?”

@sara_ann_marie, “New Forms, Old Places.”

“And you, that person out there feeling stuck, thinking that all this innovation stuff doesn’t belong to you? It’s your turn to listen up—because this next bit is all about how you can start bringing new content forms to your organization in one of two ways: bridging or infiltrating.”

@CarlZimmer, “Are Neanderthals Human?

“Paleoanthropologists cannot agree.”
via @TheBrowser

@Andrew_Zolli, “Want to Build Resilience? Kill the Complexity.”

(Pilot 1) Damn it, we’re going to crash… This can’t be happening!
(Pilot 2) But what’s happening?

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Surprise and Learning

I used to teach literature, writing, and research at the college level. Over time, I learned to pay careful attention to planning and staging the first few meetings of a class each semester, for that was my window to set expectations. There was usually a lot to clarify.

Of course, there was also a lot to bring to the surface, especially in my classes on African American literature and culture. Students in those classes were usually surprised when I arrived. I could see it: puzzled looks, quizzical glances exchanged; perhaps a bit of eye contact offered and then dropped, or a steady gaze as I went from the door to the front of the class.

I always asked them about it: “Welcome to English 264, Major Black Writers. Now, raise your hand if you were surprised when the door opened and the professor walked in, and it turned out that he was a big white guy.” Every time, at least half of the hands went up.

With that, I gave them a definition: “Surprise is the signal that you get when the world violates an assumption that you didn’t even know that you had.” And so I opened what would always prove to be one of the deepest lines of discussion throughout the class: What is the relationship between the way that we see the world and the way that the world sees us?

that is a strange sort of business, indeed

When you’re surprised, you look around to see if anyone else has that same reaction. What you’re trying to do, I think, is re-establish the validity of the assumption. If others are reacting in the same way that you are reacting, then you can feel that the assumption underlying the surprise is one that’s held in common, perhaps even held as valuable. The violation still exists, of course. But a shared surprise reaffirms the sense that the underlying assumption has validity.

By contrast, an unexpected occurrence that lacks this sort of relationship to the background ideas, values, or assumptions that make up one’s world-view would more likely be startling, and thereby provoke disbelief or incredulity. And when your conscious assumptions are violated, the reaction is probably more typically disquiet, irritation, or even anger.

In my experience, these instances are very rich learning moments that potentially expose a whole range of meta-cognitive, social, cultural, and individual mechanisms that all have in common one thing: they teach people what to expect as “normal.” Surprise is a signal that these mechanisms are there, and are closer to the surface of our lives than we often know.

Of course, there’s an element of risk in violating assumptions: they may prove to be ideas to which your audience has a conscious attachment! Paul Ekman, one of the pioneers of the study of facial expressions, suggests as much in some of his best-known research.

Ekman’s work with the Fore of New Guinea four decades ago indicated that six facial expressions are universal across human cultures: happiness, anger, sadness, disgust, surprise, and fear. When shown photographs of people from other parts of the world displaying these expressions, the Fore people that Ekman questioned consistently identified the emotions correctly, with one exception: fear and surprise were difficult to tell apart. The likely reason, Ekman writes, is that “in this culture fearful events are almost always also surprising; that is, the sudden appearance of a hostile member of another village, the unexpected meeting of a ghost or sorcerer, etc.” To be surprised was to be afraid.

In the case of the learning professional, I’d say that there will be times when we have to run the risk of looking like a hostile, a ghost, or a sorcerer, even deliberately assuming that appearance. Properly negotiated, all of us can ultimately gain through the surfacing of unacknowledged background assumptions. But learning is a risk, so we had best pay attention to as many layers of the process as we can capably track at once!

Copyright (2012) David D. LaCroix. All Rights Reserved.

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