In finishing the 2018 pedagogy course, it’s great to re-affirm the role of people-feelings within the realm of academia, be it research or instruction. It’s easy to become lost to the allure of pure, cold logic, the belief that things have definitive beginnings and definitive endings, that facts may be readily discerned with absolute certainty. Yet reading Parker Palmer’s piece shows an entirely different side to explore. Research and instruction alike are both voluntary and fallible: what may be discovered is forever limited by time and technology, what may be learned by the limitations of focus and recall. It’s important then that we draw our gaze as much to why as we would to how, that we shine our narrow vision on those gaps most worth knowing. It’s important then that, even when limited by institutional directives, we remember our true, original spirit of study, that which we dreamed about as children and which survives within us today. There’s much momentum in life which cannot be resisted, but all can be guided, and by integrating emotion into the driest, most tiring of fields, we can find and share that which is worth knowing and steer the course of the development of worthwhile knowledge for those the follow us in time.
Inclusivity is a challenging subject to discuss at times as societal morality presents a constantly moving target. The common playground insults of yesteryear become the room-silencing slurs of today. In turn, technical terms for uncomfortable subjects segue to playground insults and require routine maintenance every couple of years. This is largely great, it’s becoming more and more taboo to label individuals by aspects of their self beyond their own personal choice, and I’m sincerely curious how long it will be until pejoratives describing rural populations fall out of favor. As morality shifts more and more, we suddenly come to view each previous generation as selfish and barbaric, casting ourselves as the temporary heirs of a more civilized age. Inevitably, these positions too are shown to be folly and morality will generally continue forward as we realize and communicate more of our mistakes. As such, any statement specifically anchored to the accepted morality of a given time and circumstance runs the risk of coming off extremely tone-deaf in short order. In writing this, I question if tone-deaf is even an appropriate term.
No matter how woke you may (desire to) be, you have to run as fast as you can to stay where you are. And in a world where real, actual Nazis exist as a cultural force once more we need to keep up the pace. The notable social progress in our discourse in the last five years has triggered an equal if not greater retraction in opposition. Per the cliche, everyone is the hero of their own story, and many find it just so much easier to see oneself as a steadfast hero of free speech, beset on all sides by snowflakes than to see themselves as out of touch with time and society.
The benefits of inclusivity in academia are clear and can be selfishly justified with no presumption of altruism. We take the best and brightest from all over the world and pay them a bare necessities salary during 2-5 of the most creative, most hardworking years of their career. The question then becomes, how do we conduct inclusive pedagogy to reach both sides of the aisle, all the while functioning within our own implicit biases? For this I lean heavily upon two simple rules: don’t be a *jerk, and understand that you just might not get it, and that’s okay.
I take don’t be a *jerk from the Team Rubicon code of conduct. Team Rubicon is disaster relief organization that’s built upon a beautiful lie – that their primary business is disaster relief. While they perform admirably well in serving disaster afflicted populations, their true, unspoken mission is to rehabilitate afflicted service members. Team Rubicon deliberately recruits veterans struggling to re-adjust to civilian life and gives them a high energy, high adrenaline environment where their martial skills and dedication are useful once more. By pairing new members working to get well with elder members who have been there before they create a natural support group for those carrying hidden wounds. Given such preconditions, I was really surprised to see what a memorable and timeless code of conduct they chose to unite under. We might not realize all the ways we’re beings jerks, and no system of rules can ever keep up with our increasing awareness as a society, but if you start simple, it’s easy to maintain and build a solid foundation.
Second, is that sometimes, I just wont get it. This I take from an episode of South Park in which Stan repeatedly tries to apologize for the blunders of his father, growing more and more off-message with each attempt. Finally, after failing in every attempt to understand and right this wrong, Stan finally realizes that he’s failing because he just doesn’t get it, and he never will. There’s a lot of beauty in layers to this. From the ivory tower perspectives of academia, it’s easy to imagine that all knowledge is tangible and may be readily extracted given the right hooks. Falling into this line of thinking with regards to inclusivity risks discounting one’s entire lifetime of lived experience and private struggles. At the end of the day, somewhere in our selves, we all have some deep wound, some pernicious injury, some hole that we will spend the rest of our lives trying to fill. We can never truly understand what experiences one is carrying looking from the outside in, it’s showing that we’re willing to listen, to accept, and that we care enough that we will strive to do better, even though we don’t always get it.
These rules are simple, they don’t cover everything, but they are robust and generalizeable. Following these has led me well as a framework, and they contain a pure and simple enough truth that they may be disseminated readily – please do.
I recently had the pleasure of reading the prologue to Sarah E. Deel’s work, “Finding My Teaching Voice.” In it Deel describes her own challenges in rectifying her personal preconceptions on teaching while learning how to effectively guide a university chemistry class. Notably, Deel had to come to terms that she did not possess and could not fake the base personality attributes of the popular teachers. This piece raises interesting points on the virtues and limitations of sincerity, the selection of success metrics in one’s engagement with students, and the ability of one to take that which is valuable within themselves while also realizing the degree to which the remainder may prove limiting.
Within a challenging situation, it’s often easy to reflexively retreat upon prior concepts of self, to say “this is not me, these guys don’t get me, maybe I shouldn’t be here.” This thinking may occur just as easily within a teacher as a student. We’re all vulnerable to the imposters’ complex and while unmentioned, it seems quite prominent within this work. Whether you pick the Batman or the Count of Montecristo, it’s valuable to have an internal rags to riches/ triumph in adversity/ revenge by success personal story of inspiration. One is not an imposter in such a scenario, one is a hacker more like, hacking their way through the challenges of education from the outside with a laser focus on their true goal. Where Deel discussed her new approaches as an extension of her prior self, built onto the framework she knew well, it may be valuable to work with students in such implementable terms. By mastering a small skill in science, one may acquire greater confidence to try others. When one finds themselves possessed of diverse, science related skills, the student who just wasn’t one of those science guys might suddenly recognize the scientist within. This finding may be greatly assisted by an educators directing their attention towards those positive attributes within one which grow through diligence.
Another trend I note in Deel’s writing is the manifestation of shoulds in response to a stressful situation. Herein i define shoulds as simple unqualified beliefs about the way things are or are meant to be. Perhaps a teacher should always be commanding and have a booming voice? Likewise, perhaps a teacher should be a relatable goofball with a heart of gold? There’s only but so much room for Pattons and Patch Adams before we all tire of their antics, and within the piece Deel quickly recognized the inefficiencies of relating to students homogeneously as a cardboard cut out. Her best path to ensuring the students’ success was again relinquishing that which did not work and working to append on more positive traits, moving forwards as her aspirational self rather than her comfortable self.
All in all, this piece provided a solid description of adaptation in the face of challenge.
A recent reading of Garnder Campbell’s Post, “Curiosity as a Learning Outcome” drove me to consider the arcs and anecdotes by which I’ve observed curiosity in my own personal life. Within the post, Campbell cites 10 generalized, psychological metrics of curiosity as emblematic of the very virtues higher learning seeks to imbue upon students. An interesting extension of this would be to note the extent to which knowledge and curiosity reinforce each other, such that certain knowledge becomes a prerequisite of useful inquiry. At the surface level, we may see the fruitlessness of low effort curiosity, the 2AM infomercial inventor type. XKCD sums it up well here, whereby some people might spend their entire life thinking the one thing standing between themselves and a fabulous fate was one little nugget of inspiration, that one idea for the pet rock, that fortunate twist a friend managed to nab by sheer luck alone, discounting any sense of the journey required to reach it. Within my undergraduate studies in Chemistry, I found it interesting to see how the first year and a half was all multicolored fires, liquid nitrogen, and churning reactions. After the whiz bang theatrics, we settled into 2.5 years of analyzing very low concentrations of sundry compounds in deionized water. It was far less exciting than the years preceding it, but that space beyond the attentions of armchair inventors is where the real work and money were. I see this as a solid anology to higher education in that if one truly wishes to innovate within their field, they must possess such intense curiosity that they can work the long hours for that 5% improvement that changes their mind. That’s not to say there’s no low hanging fruit in the world, just in the 1990s we as a species figured out how to save thousands of lives a year using two clay pots and a bit of sand.
Coming from a different perspective, my experience in search and rescue shows the risks of fatigued curiosity. There is a very well known phenomena within mass disaster response that injuries and accidents happen after the second day. When first thrust into a novel and dangerous situation, our alertness is peaked, and by extension our curiosity. We scan our environment with wide and suspicious eyes, and we note everything that appears out of place. As time passes we grow comfortable, we stop asking questions, and well fall into a routine, forgetting full well that nothing about our current situation may be routine. Further, there is the question of finding subjects. As with danger, curiosity about the environment for clues and signs will often wane with time and experience.
Newly trained volunteer searchers will call stop for every out of place soda can, beer bottle, and candy wrapper. There appears to be no acre of land on this green earth lacking each of those in abundance. With time one becomes more inured to clues and more motivated to cover distance and finish tasks. During such missions it’s not uncommon to pass an old shed, a pile of debris, or even an odd patch of terrain that’s a little ways outside of the task area yet draws the mind. The stories of search subjects are often concluded before the search begins regardless of our actions, but this may be unknown to the world at large for days if not weeks, sometimes years. Given the weeks of media reminders, unsatisfied curiosity may lead way to nagging doubts or potent regrets. Therefore, whenever anyone asks “is it worth searching that?” the answer is always “yes if you will sleep better, we can wait.”
Summing these up, perhaps there’s a strategy within for crafting a potent and useful curiosity within education. It’s important to arouse curiosity with the shiny colors and whizbang theatrics, yet one must also carefully manage the following the drudgery of finesse until the excitement of the frontier. Likewise, in time within any field curiosity may wane and leave one vulnerable. A periodic sidestep into the adjacent fields may prove an exciting deterrent to complacency well worth the opportunity cost of the transition.
Recently I’ve been looking into the problem of pro-health messaging on twitter regarding the opioid epidemic. This presents a natural analogy to contemporary pedagogy as we are looking for optimal strategies to educate a population, albeit distant and often unwilling in this case. A rather important point of consideration in dong so is how effective such campaigns really are. More so, are individuals more likely to share pro-health messages if they are seen to be coming from the right source, and do certain sources carry certain messages with more gravitas?
In order to explore these dynamics, I’ve conducted a pilot study analyzing 5,403 original, non-retweet tweets collected with keywords relevant to opioid abuse. These tweets were collected from Virginia and Georgia over an 8 month span. Each tweet was manually labelled for having one or more messages regarding opioid abuse or marked irrelevant if no such messages were present. Message types included generic avoidance of drugs, discussion of health consequences, discussion of legal consequences, public interventions, reports of contamination and/ or misrepresentation of drug contents, and use witnessed/ experienced. Users profiles for tweets not marked as irrelevant were flagged as coming from individuals, social pages, organizational pages, law enforcement, public agencies, and media pages.
For each tweet, a sum potential exposure was calculated as the sum of the original tweeter’s friends and followers counts, plus the sum of the friends and followers counts for each retweet of the original. Using these sum exposures, message virality was defined as the sum of all exposures for a given message divided by the sum of the friends and followers counts of the original posters. Plotting these out, several trends become apparent:
Firstly, looking at total messages expressed, we see that individual posters, social pages, and deleted users make up a vast proportion of the bulk of all shared messages. We also see that they really like to talk about their personal drug use or drug use they’ve witnessed. Their relative proportions of messages are also quite similar. One may infer that the deleted pages would mostly represent individuals, and that social pages generally followed the structures and interests of the individuals captured within this data set, rather than adhering to organizational content guidelines.
This is evermore apparent when you compare the total messages expressed per profile category. However, an interesting thing happens when you start weighting figures by the total exposures rather than just sheer message output:
Suddenly those news pages become extremely prominent. We also note that more health-positive/ abuse-negative messages rise in weight of exposure across the board. News agencies do very well with general fear stoking, as discussion of health and legal consequences of opioid abuse flourished there. Individuals also significantly boosted the exposures for messages related to contaminated drugs. Law enforcement pages face mixed results when talking about consequences of abuse, but they do very well when conveying messages about avoidance and public interventions.
Looking back to that pi chart, once weighted by exposure we see the News category suddenly gains a large upper-hand over individuals, and Law Enforcement gains significantly as well.
Finally, we come to message virality, or the odds of a message transmitting well beyond its initial audience. Within virility, we find a nice surprise in that law enforcement pages did the best of all profile types in spreading messages with regards to avoidance, public interventions, and health consequences. Secondly as expected, news pages do well when discussing the consequences of opioid abuse. Individuals discussing what or how things should be fixed got a fair bit of representation as well in spite of their relatively low follower counts. However, while individual messages of contamination saw fairly solid exposure rates, they actually were not retweeted within this data set. This would suggest that many of those reports of contaminated drugs were made by individuals whose follower bases were great in number yet reluctant to share messages. Finally, a strong disappointment here is present within the organizational category. While there were some companies and advocacy groups within this category, most of these tweets were from K-12 public schools hosting anti-bullying and anti-drugs days to positively influence their students. As these messages showed poor virality, it seems that people really aren’t spreading these kinds of messages from these kinds of sources.
There’s a lot of take home messages from this with regards to pedagogy, and more posts will follow on the matter. I think it’s important to note that who your audience perceives you to be will have drastic effects upon how well your messages are conveyed. No one wants Law Enforcement entities to wag the finger of enforcement at them, yet when they’re perceived as kind and helpful people are extremely receptive. News agencies meanwhile do best for doom and gloom to the detriment of most other subjects. Finally, people like to feel that the experts are in control and that solutions are within reach. Posts regarding public interventions were quite successful coming from individuals, law enforcement, and to a lesser degree, news sources.
Just last week NPR published an interesting little article discussing educators’ and experts’ views with regards to the role of personal technology within the classroom. The article presented a spectrum of views regarding whether student’s access to cellphones and laptops provided a net-negative effect to the classroom learning environment. It’s easy to scoff at this question as technological conservatism. I personally recall the days when elementary school children were free to bike miles to class unescorted, yet ownership of a beeper or cellphone was an expulsion-worthy sign of poor character. The distractions were still present, those wishing to mentally escape class were free to play a few rounds of Decision on their graphing calculators. Barring access to such technology a couple chapters of young adult fiction from a hidden book could make the days go by. Truly, lacking any comparative experience from the teacher’s side of a K-12 environment, I have great empathy for the distracted students who as of yet have little to no true agency in their lives and educational participation.
Still, as was discussed in Pedagogy lecture, one must also acknowledge the very meaningful difference between such passive time wasters and the realities of the open Internet. A ten dollar burner from the grocery store now yields access to an entire ecosystem of apps optimized to capture one’s eyes as often as possible. As magazines die and consumers cut cable, we’ve grown to accept trading a little kick of digital dopamine here and there for the ad-views which make our world go round. Perhaps this beast of technology is a bit less Mickey Mouse and a bit more Joe Camel? As tempting as it may be to view this once more through a generational lens there’s much to be said here with regards to personal learning objectives. Most specifically, is one most concerned with theory or implementation?
For those theory-minded individuals who are most gifted if not pleased to conceive, recognize, and describe problems, rich contemplation on singular matters is key. While this would run at odds to distraction-prone technologies, it’s also important to consider the roles of discussion and debate. How fully formed may a theory be if it has not been contemplated via outsourced perspectives? Truly, is the classroom a simple knowledge dump where one must optimize transmission rates as one would with their wireless router? Perhaps theory is best served as hors d’oeuvres, offering lots of little tidbits to be more properly merged and ingested hours later as the mind slides into REM sleep.
Those most entertained or gifted by implementation have a much different process for digesting knowledge. They may be alarmingly unconcerned with why, yet adept at the granular nuances of how. For these students I see no reason to limit access to any personal technology within the classroom. Lets start with a few base assumptions here. While technology aids distraction, technology also enables the rapid lookup of knowledge. The Internet of social distractions is also the Internet of tutorials, open troubleshooting, and technogeek forums. Using a series of google queries an implementation-minded student may learn the entire methods behind an artistic or technical process without being bogged down by the theory of why.
This brings up a question of equitability. There’s much debate on the role of gifted-education programs, whether they uplift those admitted or suppress those not. Given access to personal technology, the most invested students may explore points of curiosity 5 steps ahead of a lecture for a far richer experience. However, are the remainder of the students differentially distracted by the open web, and does one make up for the other? Technology will always become faster, better, and cheaper. Therefore, any mainstream technology which is sufficiently workable now (I’m looking at you 2005 Google docs) will almost certainly out-pace its traditional peers later. If technological distractions have reached a robust and stable state, perhaps it’s best we accept their intrusion and await the emergence of more captivating educational technology? As computational power and open source tools grow near disposable, the opportunity for simulation and interaction grows for theory and implementation-minded learners alike.
“Inspirational Quote”
– Dead person with above-average SES and a robust social network –
References:
Kamenetz, A. (2018, January 24). Laptops And Phones In The Classroom: Yea, Nay Or A Third Way? Retrieved January 29, 2018, from https://www.npr.org/sections/ed/2018/01/24/578437957/laptops-and-phones-in-the-classroom-yea-nay-or-a-third-way
It’s happened: the joyless, workaholic millennial generation has continued its mad spree of metaphoric murder. We have slaughtered diamonds, buying houses, buying cars, and the US birth rate. Soon we may kill listicles about things millennials have killed. With single minded zeal, we’ve largely elected to stop spending money on most every non-survival imperative thing that those gifted with the comforts of time, money, and economic certainty tend to indulge themselves in.
With this in mind, I summarize my reactions and offer counterclaims to Gardner Campbell’s assertions in his 2016 piece, “Network Learning as Experiential Learning.“ Campbell’s article begins with a summary of similar views expressed in George Kuh’s 2008 monograph “High-Impact Educational Practices.” Campbell registers his agreement with the problems expressed therein whilst suggesting alternate solutions thereto, stating the problem thusly:
Education was becoming more about careers and “competencies” (a word Kuh himself used, although in a larger sense than others have) and less about inquiry, meaning-making, and a broadly humane view of human capacity. Kuh’s essay implicitly recognized that one of the great costs of abandoning these more expansive views of the purpose of higher education was that students might become alienated from their own learning experiences. He was right. Even as “student-centered learning” became the mantra, the increased attention to outcomes and objectives served (and still serves) to enable a narrowing, behaviorist focus on easily measured, easily described outcomes linked to detailed prescriptions, policies, and penalties, all contained within the course contracts (i.e., course syllabi). [1]
It feels petty to attack the article solely from this premise, but I would love if such a problem was the greatest that I had to solve. To suggest that current issues are a matter of cynical calculus or co-opted passions rather than a reflection of the larger forces at play smacks of heralding from the ivory tower. Further, there is a delicious irony in citing a piece from 2008 to contend such a point – millennials operate from the moat, ipods and nintendos be damned. The romans were able to indulge themselves with art, philosophy, and maths as they were fattened by the toils of others. This is a lifestyle afforded to relatively few millennials. The vast majority of Americans are living paycheck to paycheck, a single unexpected bill portends doom, and the inevitability of becoming ill is a challenge few of us are prepared to face.
For anyone in doubt of the dire economic circumstances facing millennials, I heartily encourage you read huffpo’s brilliant article “FML: Why millennials are facing the scariest financial future of any generation since the Great Depression.” I also strongly encourage you to share said article with any boomers, gen-x’ers , or otherwise fortunate acquaintances still beholden to the just world fallacy with regards to American social mobility. Success is an apparent zero sum game, and like medicine, it is offered at rates the market will bear, not those it needs. The spectre of technological unemployment looms before us all, and rather than sharing the bounty of past generations’ technological achievements in automation we will remain as a nation beholden to the puritanical notion that labor is the requisite exercise of virtue. Due to our knee jerk aversion to all forms of socialized good, this behavior will continue far past the extinction of such labor. When seeking to compete in such an arena, is it any surprise that we meter our efforts with respect to the potential rewards, that we who are burdened with such problems seek to develop our skill in implementation rather than our love of theories?
Returning to the article of discussion, Campbell finds agreement with Kuh and follows traditional boomer tropes in lauding free labor as an opportunity for experiential learning, citing “study abroad, internships, service learning, and community engagement” as well as undergraduate research as opportunities for students to improve their inherent value [1]. Campbell does however thumb his nose at Kuh’s narrow dedication to the more tangible repositories of knowledge and the networks therein, suggesting it be supplanted by the endless bounty of the internet. But of course, students/ millennials are once more accused of naval gazing whilst missing the spirit of the endeavor:
Yet our ideas about digital literacy are steadily becoming more impoverished, to the point that many of my current students, immersed in a “walled garden” world of apps and social media, know almost nothing about the web or the Internet. For the first time since the emergence of the web, this past year I discovered that the majority of my sophomore-level students did not understand the concept of a URL and thus struggled with the effective use and formation of hyperlinks in the networked writing class that VCU’s University College affectionately calls “Thought Vectors in Concept Space“—a phrase attributed by Kay to Engelbart and one that describes the fundamentally experiential aspect of networked learning.
Within my own narrow silo, I contend that millennials in higher education perfectly well understand the value of online networks, albeit not from the same perch that Campbell does. The human world has developed in complexity and competitiveness such that many problems are beyond the grasp of singular minds. Further, good minds are expensive and seldom loaned freely. These social networks and walled gardens Campbell dismisses are a marketplace where friendship is exchanged for the services of strong minds. Our network is our friends and colleagues who understand the theory of our problems well enough to guide us in the implementation of solutions. Nodes in this network may take the form of the veterinary student able to provide a presumptive diagnosis for an ailing pet, the statistician able to explain why our answer is meaningless at present, or the salty field-veteran whom helps us navigate the politics of publication.
If those born of more fortunate circumstance suggest you lack the spirit and gumption to see things as they did, laugh freely. If you’re not angry right now, be angry. It is far better to accept the poverty of your situation and strive forward with cynical pragmatism than to indebt yourself fighting to maintain the appearances of one gifted with a world and circumstance which no longer exists.
References:
Campbell, G. (2016, January 11). Networked Learning as Experiential Learning. Retrieved January 18, 2018, from https://er.educause.edu/articles/2016/1/networked-learning-as-experiential-learning
*Please feel free to interchange all instances of “student”, “millennial,” and “those darned kids” at your leisure
The following blog post presents a project completed for the 2017, Preparing the Future Professoriate class at Virginia Tech.
[themify_hr]
Project Goal
Mentorship presents a profound part of the experience of academic research. A mentor whom provides guidance and wisdom may earn our lifelong admiration. A mentee who struggles to succeed may earn our compassion; one who fails, our empathy; and one whom succeeds, our greatest pride. While most researchers will work closely and develop strong relationships with their PIs, it’s important to recognize those interstitial mentors. Those who may have helped us to fix a thorny bit of code, to procure a prized analyte, or to assuage the whims of an ornery administrator.
In this project I sought to identify these networks of proximal mentors, providing a means of charting the flow of knowledge and wisdom through an academic organization. I also sought to make them beautiful, visualizing these organically grown relationships via a natural metaphor. Initially I had planned to craft these trees from individual user’s networks, serving as a sort of mirror into their professional life and the academic pedigree from which they had hailed. I was hoping to see a tree which fanned out laterally to a wide breadth of unrelated talents and applications, yet drilled down historically to a surprisingly singular expertise. Still, as more and more progress was made in crafting the trees, viewing the development of a cohesive organization both in its individual members and its missions became a more interesting challenge.
The presented visualization draws from a coauthorship network of the laboratory where I work, the Network Dynamics and Simulation Science Laboratory (NDSSL) of the Biocomplexity Institute of Virginia Tech. I had initially considered using the publication history of the members of the 2017 Preparing Future Professoriate class to construct this network but decided upon the NDSSL as its member and publication list could obtained without utilizing privileged information. The code for this project may be used under the terms of the GNU general public license and is generalizable to any coauthorship network.
MentNet Capabilities
Identify proximal mentors within a coauthorship network
Identify and collect mentor-mentee publications from pubmed
Automatically Categorize primary publication topics within a research organization
Development
The first challenge in creating MentNet was identifying a pleasing aesthetic. Just as elementary school classrooms are littered with cheery, inspirational posters to motivate young students, I wanted to create something that would appear beautiful, would show the complexity and structure of an organization, but which could be appreciated on a purely aesthetic level. I wanted to construct the visualization in such a way that viewer would feel no pressure to analyze it, that it could merely be taken as an intricate metaphor absent obligations to function or practical utility. As trees presented an obvious structural metaphor, randomly generated dummy trees were generated and rendered via python matplotlib axes3d objects to test this. Trees were defined by the mean relative length and angle dispersion of off-shooting branches respective to their origin branches.
A sample dummy tree may be found here:
A coauthorship network queried from the NDSSL content management system (CMS) by Dr. Stephen Eubank was used to create the base network [1]. This may present some challenges to the generalizability of the resulting code, though it would be trivial to create novel coauthorship networks given access to a collection of papers from a given laboratory or discipline. Per the advice of my advisor, Dr. Bryan Lewis, future efforts may explore just that, seeking to establish the flow of knowledge across the fields of public health and epidemiological modeling.
Here is that underlying coauthorship network:
Once the coauthorship network was obtained, the next challenge was identifying proximal mentors. The network was loaded within NetworkX and each node within the network was labelled with its betweenness centrality. Beetweenness centrality is a measure that states how often within a given network the shortest path between any two nodes may cross a given node [2]. Of course, per the proximal mentorship idea, the individuals within the network with the highest centrality generally ended up being primary investigators and funding partners. A quick algorithm was written that identified each individual’s proximal mentor as their neighbor which had the lowest centrality which was greater than their own.
Incorporating this metric, we create the following: (image)From here a true(r) mentorship tree was created using a slight modification of the dummy tree creation code. While the basic network represented within the tree remains constant, the structures are randomly generated to suit the aesthetic. As such, several test trees were grown until a selection with pleasing aesthetics was found and saved.
The next challenge came in adding leaves with maximal symbolic content and information density. A pubmed query was run for each researcher in the network to collect the abstracts of the 20 most recent papers they published with their mentor [3]. From these a superset of abstracts was collected and categorized via latent dirichlet allocation (LDA) [4,5]. LDA is a statistical model for explaining unobserved similarities within sets of data. In this case, LDA was applied to a vector of the most frequently occurring, unusual word within each abstract. From there, the algorithm identified the ten most important categories as follows:
{'0': u'influenza vaccine health social pandemic measures distancing strain transmission research', '1': u'pylori gastric responses infection cell host response immune regulatory cells', '2': u'ppar cells mice expression inflammatory aba cell immune induced disease', '3': u'patients high activity study risk pei hospitals mortality frailty clinical', '4': u'cells cd4 th17 itreg differentiation ppar\u03b3 networks modeling study regulatory', '5': u'network model networks contact based population epidemic models results knockout', '6': u'text formula using parameters large model based modeling time used', '7': u'dose 10 disease effects brain data group rates studies results', '8': u'stock flow failure health energy human subjects weight care training', '9': u'disease health data public human africa ebola outbreaks outbreak provide'}
Each paper (leaf) written by a mentor mentee pair was color coded based upon its transformed categorization via the LDA algorithm. Likewise, the transparency of each leaf was set by its year of publication where more recent papers were rendered as more opaque. It’s important to note that, while 866 abstracts were pulled via this method, many more leaves may appear on the tree as singular papers may be matched to multiple collaborating mentees of a given mentor.
From there a script was written to render the scene via a change of season motif. Starting in 1980 before the first publication, time moves forward to 2017 with bright flowers gradually appearing on the tree during their year of publication. From there, seasons progress from spring to summer as the pink flowers are replaced with green leaves. Finally, as fall hits, the leaves slowly fall from the tree, fading away on the ground and revealing the identities of each researcher where once they had been. One of the biggest challenges of this entire process was that matplotlib axes3d does not account for true spatial overlap, only rendering objects in the order in which they areplotted. As a proxy to this, the zorder of each object is set to the inverse of the distance from its midpoint to the observer. There is some distortion in the rendering of overlap as the axes are not rendered to scale, though the effect is mostly intact.
Once all images were created, an mp4 animation was generated on the command line via imagemagick’s convert function.
The jupyter notebook source code for this project may be found here:
V3 of the GNU General Public License may be found here:
https://www.gnu.org/licenses/gpl-3.0.en.html
The video may be found here:
References:
Fwd: INformation to Ms Pierre [E-mail from S. Eubank]. (2017, March 27).
Franceschet, M. (n.d.). Betweenness Centrality. Retrieved April 01, 2017, from https://www.sci.unich.it/~francesc/teaching/network/betweeness.html
National Center for Biotechnology Information (NCBI)[Internet]. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information; [1988] – [cited 2017 Apr 08]. Available from: https://www.ncbi.nlm.nih.gov/
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan), 993-1022.
Grisel, O., & You, C. (n.d.). Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation¶. Retrieved April 07, 2017, from http://scikit-learn.org/stable/auto_examples/applications/topics_extraction_with_nmf_lda.html#sphx-glr-auto-examples-applications-topics-extraction-with-nmf-lda-py
Higher education has changed continuously throughout its millennia or so of existence. Cynically, it has provided a proving ground for the wealthy to secure their roles and stations. Optimistically, it has provided a societal beacon for the creation, accumulation, preservation, and dissemination of knowledge and ideas. In toto, these goals have long run their course and the degree to which they are satisfied contributes significantly to the relative renown of a given university over time. We run as fast as we can to stay right where we are.
As we look towards the future of higher education, many things will change and many more will remain the same. Will universities as we know it dissolve, yielding to an amazing array of Massively Open Online Courses (MOOCs)? No, beyond their tendency to fall into the crispr drawer of good intentions, they lack the requisite social capital of universities to stand out on a resume. From etsy to youtube, crowd sourcing technologies have an unfortunate tendency to create few winners, perversely driving massive buy in from the remainder due to the intense visibility of said winners. Perhaps a brilliant and single minded individual possessed of undeniable talents may leverage such resources for career development, but they will unfortunately face an uphill battle against those with the proper meritocratic pedigree and buy-in to the given system. I wish them the best.
Another interesting trend is the focused coding academies and boot camps. I differentiate these from massively open online courses in that they present a more tangible bill of goods. Rather than scrapping together a portfolio of interesting and potentially useful classes, a graduate of such programs presents a known quantity. They may more readily be compared to past graduates and in turn curry reputation for an entire program. This presents a far more modern take on the trade schools of yore, specifically delivering the required talents and rigor absent the surrounding infrastructure of academia. As college debt loads show every notable signifier of a bubble and as technological obsolescence rapidly approaches many more classical trades, these are very much worth watching.
As interesting as it is to predict what may happen, it is also very important to dictate that which must not. Most significantly, we cannot let passing, idle minded, nativist narratives turn back the clock on the diversity of our academic community. There is this common myth of the immigrant stealing jobs, that the manual laborer’s value in the field may be diminished by poorly compensated immigrants, or that the international student researcher blocked a hard-working american from enrollment. The unskilled labor argument may be defeated morally by calling for fair wage and hiring practices, practically by accepting the burgeoning realities of technological unemployment. The moral arguments for permissive hiring and immigration of skilled workers are known, well stated, and received mostly upon partisan lines. Rather than waste efforts preaching to the choir or letting such arguments fall upon deaf ears, let us focus upon the selfish practicalities of retaining such students:
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1. We accumulate the best and the brightest:
Meeting international students is an efficient way of granting oneself a very warped view of their home turf. Given the immeasurable hurdles in reaching and securing a place within a university overseas, we have a very strong selection bias in place for recruiting the best and the brightest that the world has to offer. There’s an old belief that a society of Einsteins could not function, that no one would dig the ditches or staff the factories. Personally, I believe such a society would simply invent technologies to solve such trivialities. We stand to lose nothing by drawing such people and giving them incentives to stay, to work, to develop technologies and industries, and to weave themselves into our national tapestry.
One lingering question of morality here is one frequently levied against both gifted education programs and special ops fighters: by concentrating talent in narrow pools, do we see more gains from promoting talented individuals or does their absence merely depress the development of their peers’ talents? I suspect the latter yet prefer the former. Still, per individual motives, newborns sign no contract proclaiming their destiny as a citizen of their birthplace. It is in all of our best interests that we not be beholden for life to the whims of misguided home regimes.
2. We get far more than what we pay for:
During the projected 5 year course of doctoral education, students work long, tireless hours on the development of new technologies and knowledge. This is often guided by the real world utility requirements of federal grants. Not only does graduate education select for the best and brightest from home and abroad, it also keeps them here for surprisingly affordable salaries. According to GlassDoor.com, graduate student assistantships in the United States pay roughly $28k per year. For this price universities get to keep the bulk of the brilliance, the papers, and the intellectual property of students for the span of a degree program.
3. We preserve our renown:
How much is a dollar worth is a simple question. How much is a bitcoin worth, not so much. How much is an American education worth though? Like most things in life, a simple metric may be that it is worth what people are willing to pay, and the ruling class across the world have shown themselves time and time again to be willing to pay top dollar. We do much to undermine our national prestige when limiting our pool of candidates and speakers by arbitrary and capricious geometries scrawled across the globe by long-dead madmen. As the children of the international elite come to american universities to receive an american education, the inevitability of nepotism dictates that their next generation of rulers will also be steeped in American culture and sympathies. This is an advantage we would be wise never to squander; Mickey Mouse has done far more for American diplomacy than any ambassador could ever dream of.
4. We sustain partnerships:
Collaboration is key to science, most of the low hanging fruit have already been picked, and world-changing discoveries may often require more specialized knowledge than can be tidily constrained within an individual mind. For those international students who return home afterwords, not only do we retain their findings and our garnered sympathies, we retain their friendship as well. Fostering the development of international students provides an efficient means of seeding our network with diverse pools of talent and access. An open line of communication between distant universities could prove the key in saving thousands of lives during an epidemic. It could also assure favorable trade and early notification of key innovations enabling the growth of more complex industries. There is nothing to be lost by knowing more people in more places.
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I hope that in writing these thoughts, there be no confusion that this is anything more than a willful exploration of selfish justifications for inherently just behavior. The international community of Virginia Tech has provided some of my most treasured friendships, the strongest collaborations, and my fondest memories of my time here. Many things will undoubtedly change in the future of education and I would hesitate to claim a firmer grasp on the crystal ball than anyone else. It’s important that we remember where we came from and what we value, and moving forwards it is my most fervent hope that we continue to value the strong contributions which the international community makes to Virginia Tech every day.
Howdy all, in this column I begin an {n} part series exploring ideas and code of mine that for one reason or another did not pan out. It’s important to note that none of these ideas were directly tied to my research and funding, though any could have found their way in pending better results. These posts will broadly represent blind explorations of tools and concepts outside of my discipline in an attempt to broaden my repertoire. In each entry I will explore the basic idea, why I tried it, what design considerations I made, and why I considered it a failure. I will also link or will embed the source code for others to experiment upon with attribution under the GNU general public license.
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This chain of fail follows a more winding path from the others. While the PRSLearn and home automation fails began with singular, tinkerer’s goals, those following hit a little closer to home. While the previous projects were deemed failures due to structurally falling short of designs goals, that which follows failed due to sentiments and false hypotheses. Perhaps there is something to be learned from the comparison?
VAFirstResponderNet
Volunteer first response agencies suffer a significantly high burnout/ washout rate. The labors involved are neither easy nor routine and some of the inherent stressors may quickly and efficiently disavow one’s illusions of a kind and just world. Some will reject this quickly, some have the stomach for it, but I fear many may experience a slow indigestion from poorly processed memories and exposures. Per my interest in first response, I’ve been contemplating whether my laboratory’s epidemiological methods could provide some insight in identifying and assisting those dealing with critical incident stress.
Looking for convenient metrics and low hanging fruit, I wondered whether less socially integrated responders might fare worse during a critical stress incident. If we could blindly and computationally identify members who interacted within the team at a reduced rate, perhaps we might know to keep a better eye on them to offer support more readily when needed? Borrowing from network theory, a convenient metric for this might be one’s degrees of connectedness and centrality within a given social network. Facebook provides a rich source of this data, but initial proposals to mine this information were recieved poorly. The perceived slight to an agency’s privacy was taken in heed, and I set out exploring the facebook API to see whether such data was truly publicly available.
It wasn’t. It could have been collected with individual app permission requests which would almost certainly surpass one’s threshold for creepy. It also could have been collected with a pen and paper, manually compiling a web of individual’s in-group network edges. But, as such access would depend on privileged, non-public relations, it would certainly violate the spirit of those relations and this idea was scrapped.
The question now became whether anything useful had been constructed along the way, and whether the developed tools would be more appropriate for a different task. I hammered out a quick crawler script for public facebook groups and pages. The idea would be to take a set of keywords, group types, and geographies, start with a seed page, then slowly crawl its network of likes and liked-bys until every page matching the query set had been found. I took first response agencies as a general sector of public interest which would likely maintain a facebook page and could potentially prove useful later and created the following network:
controls in bottom left, hover over nodes for information
It’s pretty, but it’s not yet useful. Maybe the highly central, red to yellow agencies could prove rich ground for testing technologies and innovations? I’d certainly wish to talk to them first if I was selling equipment, but I don’t sell equipment. The idea remained a curiosity and sat on the back burner for a while.
Southern Soma
Years ago in a chat with a fellow futurist colleague I pondered “how long until we invent ourselves out of jobs and sit around taking soma all day?” My colleague responded, “it’s already happening dude, do you mean the rural meth epidemic?” Well in 2017 we are staring down the dual barrels of a meth and opiate epidemic as well as a general spike in blue collar deaths of despair. The factory jobs aren’t coming back, the retail and transportation sectors are gazing into the abyss, and the canary in this coal mine will be well and truly dead before our national culture ever dares to acknowledge the utility of a mandatory minimum wage.
The modern opiate epidemic presents a crucial challenge to public health; it’s nature as an economically driven disease of despair defies easy solution. One glimmer to a potential trail of causation appeared via the 2017 Appalachian Studies Conference. A poster by Carillion researchers mentioned pain management following occupational injuries as a pathway to addiction in blue collar, rural communities. I’d had my own run in with chronic pain following a torn meniscus during a rescue call. Absent proper treatment, its condition had slowly worsened for about a year before hitting a second injury which landed me in physical therapy. PT was miraculous, almost every notable marker of pain and performance significantly improved over the span of a month until I had returned roughly to my prior state. Taking this in the context of the opiate epidemic I wondered, if occupational injuries are a stepping stone into addiction, could physical therapy present a viable intervention? Short term pharmaceutical management of pain would undoubtedly be cheaper than time with a trained therapist, and one could easily imagine that such would present a perverse incentive for insurers. Maybe some communities would resist such incentives and have greater access to physical therapy, maybe this would even grant a preventative effect?
Quantifying Access
With these questions in mind, I set out to conduct a preliminary analysis of whether or not differential access to physical therapists proved protective against opiate related morbidity and mortality across rural Appalachia. I defined access as the number of physical therapy clinics in a county per 10,000 people. As offered by my friend and colleague Alex Telionis, a more comprehensive study could have sought mean population travel time to physical therapists, but this was truly just a test of plausibility. Per a negative outcome, after asking the facebook hivemind for suggested markers, I decided upon CDC county mortality stats per the wonder database.
My first attempt to quantify the number of physical therapists per county was to reuse the facebook net crawler from the first response agency centrality graph. I picked a physical therapy clinic as a starting point and pulled all pages from the United States with a category of physical therapist that were connected to the outlying like network of the starting therapist. The resulting network may be found here:
controls in bottom left, hover over nodes for information
These results were lacking, offhand testing showed numerous area therapists simply weren’t visible on this network. I could easily imagine that on a local scale we might have isolated cliques via rival provider networks. However, zooming out far enough, you’d imagine that at least one smaller, private facility or agency would have attempted to curry favor with both sides, thereby connecting different agencies to the total graph. A more obvious conclusion was that physical therapists just weren’t that into facebook, moving on.
Scraping the web
Lacking an easy source of PT clinic geolocations, I trolled the web and hit the hivemind once more. Many states keep professional registries of clinics, but these are often independent efforts that would require a significant amount of paperwork, registrations, and parsing to incorporate. Framing this as a curiosity project, there was just no way to requisition this much time without any initially promising findings. I reached out to some national registries and associations to see what they had to offer but the results were likewise discouraging. Then I stumbled upon everypt.com. Checking their terms of service, the registry was open for informational and education use, bingo! I threw up a quick webscraper with beautifulsoup to pull down clinic addresses across Appalachia, geocoded them to coordinates via the python geocoder library, and matched them to tiger shapefile counties via geopandas to get a clinics per 10k count.
Quantifying Mortality
The next task was to quantify the negative effect of opiates on a given area. I went with mortality as it was likely to be more reliable than any publicly available figures of ongoing abuse or addiction. I can’t imagine individuals are likely to disclose their addictions to a reliable and consistent degree across territories, nor do I imagine that municipalities or practitioners are consistently incentivized to publish their opiate throughput, but dead means dead. I went with the CDC Wonder mortality database and ran a query pulling county level age adjusted death rates for working age men and women from HHS regions 4, 3, and 2 ~ a geography containing the bulk of Appalachia. Within these, I picked a subset of counties marked as micropolitan and non-core by the 2013 urbanization index, here used as a proxy for rural. Beyond my concern with blue collar populations, the hypothetical interplay between physical therapy and addiction could have been completely different in nature between rural and urban regions via employment types, insurance coverage, and cultural considerations.
The next challenge was in crafting a case definition for mortality due to opiates. Looking through the ICD-10 codes, the F11 codes seemed to provide a pretty strong catch all for opioid mortality. I submitted the query and received.. almost nothing. A small handful of county stats were returned with most marked as unreliable. Coming from my experience surveilling public social media posts, it was a potent reminder that privacy matters. All counties with less than 20 deaths in a given time frame were removed from the results to prevent unscrupulous researchers from re-identifying individuals. As I was looking specifically at regions with low population densities, such a quantity of overdoses would have bordered on the apocalyptic. For now, the entire bottom quantile was removed from my data set and with an n countable offhand, no meaningful insights could have been interrogated from this data.
Mission Creep
Still eager to see some sort of connection I resorted to broadening my case definition to get past that 20 case limit. I hit every opioid related ICD-10 mortality code, I boosted the year range of the data to 5, 10, and 15 years in succession, and I boosted the age range to all adults. The results were negligible, the correlation was both weak and negative, and countless counties lacked any form of clinic. This goose was cooked. I could have further tweaked the data, perhaps stratified it differently or re-evaluated my case definitions. I also could have looked into fitting a model to the case counts and back predicting numbers for those sanitized counties as was done with this recent Zika study. But really, it’s just a negative result on an analysis borne of curiosity. I’d already delved as far as I was willing to go into the dark side of data mining and would almost certainly induce bias by going further. Further, going back beyond 5 years would likely induce severe flaws due to changes in local conditions, clinic access, and cultural contexts for addiction.
Sad pandas
The lessons
It was interesting to see how the scrapers came in for both cases. People may complain about social media being noisy and unreliable, and it is, but there is no such thing as perfect data. The blessing of public health is that we’re not looking to prove a theory or discover a particle, we’re fireman trying to stamp out our epidemics. If something can be done a little better or a little faster than before then it is inherently worth doing. It was actually shocking how complete and accurate the first responder net was, as those pages not created privately by the agencies were often manually created by the community, complete with up to date location data. This could prove invaluable for quite a few scenarios. In the event of a large scale crisis, having a geocoded map and contact numbers for all the hardware and big box stores could prove invaluable for resource allocation. Likewise, in the event of a suspected common source outbreak, identifying and locating all franchises in an exposed chain may prove useful.
There were quite a few flaws in my approach to the opiate study owing to my time constraints. As stated before, seeking the number of practitioners per 10k rather than private clinics would have been a far better metric as many practitioners travel for in-home care. Second, small rural counties may simply lack the population to sustain a dedicated clinic, seeking their care either through local hospital practitioners or through adjacent counties. Third, who is to say all clinics are on the same level? Someone is writing these prescriptions, to assume that all clinics involved in pain management are playing on the side of the angels may border upon naive.
Finally comes the question of data mining. I’m pretty ambivalent on the idea as a whole, though it’s certainly a source of division. On one had, we have vast pools of data and zippy tools that were simply not available before and we’d be fools not to use them. On the other, if you publish a thousand data mined studies with a 0.05 p-value, you just wrote 50 completely false conclusions. These conclusions may inform the development of drugs and the deployment of safety measures. They may squander the funds of more efficacious programs as well as the already dwindling faith of the public. As with ChatterGrabber, I’d consider such mined and scraped data sources as an alarm system, a signal that something may be happening and the ground truth must be known.
References:
2015 TIGER/Line Shapefiles (machine – readable data files) / prepared by the U.S. Census Bureau, 2015
Centers for Disease Control and Prevention. CDC Wonder. http://wonder.cdc.gov/. March 2017.
(n.d.). Retrieved March 17, 2017, from http://www.everypt.com/
