Liveblogging RIT’s FOSS projects class: initial questions for community spelunking


Stephen Jacobs (SJ) and I are co-teaching “Project in FOSS Development” at RIT this semester, which basically means “hey students, want to get course credit for contributing to a FOSS project?” The class is centered around 5 project sprints of two weeks each. The first 3 weeks of class are preparing for the sprint periods; the week before spring break is a pause to reflect on how sprints are going. Otherwise, class efforts will be centered around executing project work… (aka “getting stuff done”).

From the syllabus (http://bit.ly/rit-foss-projects-syllabus-2018):

This course is a studio-centric experience designed to immerse students in the praxis of FOSS (Free and Open Source Software) communities. Notice that we focus on praxis, which is a conscious enactment of practice deeply informed by theory. In other words, it’s important to be practitioners who can think about their shared practice.

Notice also that we talk about the praxis of FOSS communities, which includes but is not limited to software development — ways of communicating, collaborating, designing, testing, marketing, budgeting, meeting, etc. are just as much a part of FOSS (and software engineering) praxis as writing code. You will be creating FOSS software, and you will be engaging with the rhythms, relationships, and routines of an established FOSS community with a complex set of sociotechnical dynamics that exist independently of yours. It is our hope that this course will help you navigate the kinds of delightfully messy, large-scale, long-term projects that you will encounter out in the real world.

I’ll be liveblogging the class, as one does. Right now, students are working on their project proposals, which is a big messy task that involves spelunking into existing FOSS communities, figuring out what’s up, and thinking about what’s possible to accomplish during the course of the semester. During our last class, we collaboratively brainstormed a list of starter questions we want to find out while doing that initial community spelunking. I was impressed by how much the students were already thinking about sociotechnical dynamics (instead of just starting to myopically look at the code in isolation), which makes me super happy.

Here’s what we came up with, in thematic clusters.  You can think of these as guiding questions for a spelunking quickstart such as http://blog.melchua.com/2010/10/08/possesa-fri-5-minutes-of-improvisation/ (basically, if you only had a few minutes to get a sense of whether you wanted to contribute to a FOSS project, what questions would be the highest-priority ones to ask)?

  1. What are we gathering around?
  2. What are the goals and the roadmap to get there?
  3. What’s the purpose of the project? Do they have use cases?
  4. Why should I want to contribute?
  5. How do I find people and information and ask for help?
  6. How do they communicate? Do they have forums, chatrooms, mailing lists, etc. and how can I start lurking?
  7. Who’s leading it and who’s working on it?
  8. What is the governance/leadership structure? How do decisions get made, and how fast?
  9. Do they have local meetups and/or online ones I could attend?
  10. How complete are the docs?  Where do I go and what do I Google if the thing I want isn’t in the docs?
  11. How thoughtful have people been about the contributor experience (and do I want to have that contributor experience?)
  12. Do they have a code of conduct? How good is it?
  13. Do they have contributor guidelines?
  14. How well do they Onboard?
  15. How can I help and what skills do I need? (Can these questions be answered easily?)
  16. What does the code activity look like?
  17. What’s the infrastructure?
  18. What is the license? (Make sure it’s actually a FOSS project.)
  19. What and when was the last commit to a core repo?
  20. What/when was the latest release and how is it working?

What goes through my mind on the first day of teaching as a faculty member


Today is my first day of teaching as a faculty member. I am nervous, woke up early (read: couldn’t sleep), and forgot to eat breakfast because I was so nervous I ran out the door without grabbing the food I’d planned. I spent way too much time stressing out about what I should wear so I would look not-like-a-student, but not like a boring professor (whatever that means), while still being comfortable, while… actually, I’ll just wear the same outfit I’ve worn for all my interviews in grad school ever and just leave off the jacket, because… I know it looks good, or at least the colors don’t clash. Okay.

I feel so very underqualified, and am constantly wondering “who thought it was a good idea to let me do this?” I know this is an emotional reaction and not a logical one because I’ve been teaching undergrads since 2004 and my rational brain is telling me that, by all signs (including lots of overwhelmingly positive student comments through the years), I’m pretty good at it. But. Still. Feelings.

I’m struggling with the feeling that I should redo all the course materials!!!! for the stuff that I’m inheriting, to… y’know, make it better! As if, somehow, revising my syllabus would change students’ lives!!!! Intellectually, I know that actual student gains from a last-minute couse overhaul would likely be minimal, and that the more likely outcome is that everyone would be confused, I would die of exhaustion, and zero other work would get done. I’m making peace with doing an okay-ish job of super-quick teaching prep that leans heavily on material I’ve inherited from the past, and then being really awesome and present in the classroom when I’m with my students. My teaching isn’t going to save the world. (At least not this semester.) And I’m learning (wrestling with) how to be okay with that.

Did I mention that I feel underqualified? And that I don’t want to mess it up? And that I’m worried — even if it’s a slight worry — that I’ll somehow fail students, and everything, and everybody, and… thereby demonstrate that I am Not Ready To Be A Grownup? I mean, I didn’t even take this class in undergrad! Again, not logical responses; rationally, I can teach this, but… my lizard brain is telling me to flee and stress-eat cookies and ice cream. Which I might do tonight regardless.

I have been told that all these feelings and thoughts are completely normal. And I think they are, and I’m not worried (I mean, okay, I am worried, but I’m not worried about being worried). But I wanted to write this down on my actual first day of teaching as a faculty member, so that (1) someday, when other new faculty look at me with the same kind of mild panic in their eyes as I have now, I can point them to this post and say totally normal, I felt this way too… and also (2) so that if I do end up going down in a fiery explosion and turn out to be the WORST TEACHER EVER, I can say “I told you so.”

I’m gonna hope for (1). We’ll see how this all goes.


Seeing myself in the (literal) mirror at NTID’s IT office


Some of you already know (and my previous blog post has hinted) that I’m working in a Deaf environment for the first time in my life — the Center on Access Technology (CAT, pronounced like the animal and signed as an acronym) in Rochester, NY. There’s far too much to say about this — I am glad to be here, it’s an incredible learning experience, and I often feel like a stranger in a strange land… but if there’s anything my training in writing and qualitative research has taught me, it’s the power of vignettes and thick descriptions of small moments. So that’s what I’ll start to share. This one is a very small moment, but it was one of the first things that struck me.

So I’m a new faculty member, trying to figure out how one connects to internet, printers, and so forth, as one does. I’m hitting snags, so I walk over to the IT office inside NTID (basically, the Deaf college within RIT). As I’m waiting for the IT staffer to fiddle with my laptop and fix my connectivity issues, I look around. It’s an IT office, full of familiar-looking cords and bins and tables of acronyms pinned to the walls. I see the student workers perched in front of monitors, typing into a ticketing system.

And then I notice that all of the desks facing the wall have mirrors on that wall, behind the monitors. And my first thought is “oh, that’s nice – I guess it makes the room look bigger.” And then one student walks up behind another and begins to sign, and the second student turns around to smoothly engage them. And I suddenly remember: they’re all Deaf, too.

Like me, they can’t hear footfalls from behind. Like me, they would startle from their monitors with a sudden touch on the shoulder. The mirrors let you see someone approaching from behind, a gentle nudge of motion in your periphery, the visual equivalent of footsteps walking up. And all of this is set up so matter-of-factly, just… how it is, of course we put mirrors behind our monitors! and not as some odd flustered accommodation that treats me as a conundrum in the hearing world (“well, Mel can’t hear footsteps, because she’s deaf, so what do we do?”).

I’m used to having my existence in hearing spaces not forethought (“it never occurred to us that a deaf person might be interested in this event, so we didn’t make it accessible”). I’m used to having laborious forethought be the best-case scenario, where I’m a solitary trailblazing oddity (“we’re open to setting up captions for this; can you do the setting-up in your copious amounts of free time?”). It is strange to be in a place where my individual existence doesn’t need to be forethought, because the space has already been created and inhabited by — and expects to see more of — people like me. It is strange to, at least in this one significant way, not be the Other.

Of course, it’s more complex than that. Even NTID is by no means fully accessible (likewise with Gallaudet). The Deaf (and hard-of-hearing) communities are not homogenous; not everything meets everybody’s needs. I’m not just Deaf, I’m lots of other things as well, and many of those things are still unexpected, unanticipated, not-forethought. There’s a lot of solitaire trailblazing work to do here still.

But dang. A world that is accessible to me regardless of whether I’m there or not? A space that stays Deaf-friendly without me, whose Deaf-friendliness is not dependent on my constant nudging and performance of my life as a reminder that people like me exist? Approaches and solutions that go beyond the things my friends and I can think of on our own?

Whoa.


Talk notes: “Technologies that wake you up” from a DHH perspective


Today’s accomplishment: giving part of a (group) talk in my 4th language, and making people laugh both directly and through an interpreter. Watching the audience grin and nod and crack up in two waves was just this… super-gratifying experience — first the audience members who knew ASL, then the ones who were listening to the interpreter translate my signing into English, and I could just… track that.

Sure, I know there are still all these dysfluencies in my sign production. I’m not fully fluent yet, and I’m incredibly aware of that, and working hard on it. But to know that my personality, my sense of humor, can come through in ASL even to people who don’t sign — that’s a tremendous milestone I was afraid that I might never actually reach. It’s difficult to understate how personally significant this accomplishment is for me — I’ve gone from “I will never learn sign language! I’m not one of those Deaf people!” to “I mean, okay, I guess I could learn it as… another language, because interpreting gives me so much that I just miss, but… I’m always going to speak for myself, especially in a work context with hearing people around,” to… well… this.

My talk notes follow. I wrote them, memorized them, and then deviated from them (as one does). The larger context is that my lab (which is basically a Deaf engineering design firm) is doing a series of consumer technology reviews. These aren’t technologies specifically designed for DHH people, but rather everyday technologies from a DHH perspective. For instance, other colleagues looked at various items from Nest, Alexa, etc. — and did you know lots of these devices, even if they are visual, feature an audio-only setup? Annoyance. Folks had to keep calling over their hearing spouses, ask their kids to come over and put on their CI, etc. in order to just get through installation.

Anyway, my segment was on “technologies that wake you up,” because… well, I don’t own a house. And a substantial portion of our community is made of students. And I sleep super deeply, and get uber-grumpy when I’m woken up against my will — just ask my parents; this is a lifelong known cause of Grouchy Mel.

  • most alarm systems are designed for hearing people and are based on sound
  • obviously doesn’t work so well for DHH
  • known problem: historically, all kinds of solutions – rube goldberg contraptions that drop heavy things, hearing humans (hi mom!) who will wake you up at the appointed time, praying that you’ll wake up before X and not be late
  • but now we have TECHNOLOGY!
  • I’ll examine several more modern systems for waking up DHH sleepers
  • First: Can I use “hearing” alarms and somehow make them better?
  • Residual hearing: amplify! plug into speaker system… okay, maybe this isn’t so great for hearing housemates, and it still doesn’t wake me up all the time.
  • Mechanical-only solutions: put phones inside convex objects to concentrate/amplify the sound. Definitely not loud enough for me.
  • Okay, another mechanical solution: set a phone alarm to vibration mode, put on a thin and hard-walled hollow clattery object and close to the edge of stuff that makes noise when other things fall on it. Yeah, terrible idea. Not the most reliable solution, good luck getting up in the middle of the night without wrecking everything, and an alarm that relies on literally dropping your multi-hundred-dollar phone on the floor every day is maybe not the wisest.
  • Enter: specific devices! This is an alarm designed for DHH folks… how many of you have the Sonic Alert alarm clock? (hands go up)
  • Wakes people up in three ways: audio, the sound is customizable (frequency-set knob, volume-set knob)
  • “light flasher” which is an on/off outlet flasher, could plug anything in there
  • “bed shaker” which is an off-center load on a motor in a case (like cell phone vibrators)
  • It’s definitely effective at waking you up. Abruptly. Might not be the best for your mood for the rest of the day, but it works. (Insert explanation of sleep cycles here, with a lot of hamming it up)
  • Okay, but how about stuff that isn’t DHH-specific? Sound aside and vibration/tactile aside, what’s left as a way to wake folks up?
  • Smell and taste might not be useful for alarms (although the smell of tea makes me super happy when I wake up)
  • What’s left is sight
  • Did you know: most deaf people can see
  • Did you know: most hearing people can also see
  • Did you know: although sound might not work for both hearing and DHH folks, light might work for both
  • This is the idea behind the Philips Wake-up Light
  • Idea: you know how the sonic alert wakes you up abruptly? this wakes you gently, like the sun coming through the windows
  • You set the time you want to be awake, and for a period of time before that, the lights will gradually turn on so that you’re sleeping more lightly and close to waking by the time the alarm rings (with the lamp at full brightness)
  • Gentle light wakeup is amazing (display, in contrast, the book cover of Alexander and the Terrible Horrible No Good Very Bad Day)
  • Except that it doesn’t always wake you up all the way, so you need a last-minute push-over into full consciousness
  • Alas, the pre-recorded audio settings on this alarm consist mostly of birdsong (from my perspective, “silence 1,” “silence 2,” “silence 3,” and “silence 4″)
  • I personally need a separate alarm to make the startle sound/vibration/light at the appointed time, but the wake-up light does get me to the point where being woken up by something else is pretty pleasant
  • Not a DHH-specific access issue, but the UI for button placement stinks
  • Alternative, if you already have Philips Hue lights: hack the Hue to be a wake-up light
  • Program the Hue! set something to turn on gradually at an appointed time
  • Not as smooth as the Wake-up light, which starts from zero and smoothly goes up; definitely turns on abruptly and is a more jarring wake-up
  • For me: solves the problem of “the Wake-up light needs a tip-over”
  • And then Sonic Alert for mega-uber backup.
  • End the talk somehow and turn the floor back over to Brian.

The CAT Lab Abstract Sorting Hat, Version 0.1


Another post based on stuff I came up with for my lab on the spur of the moment. I know I’m probably reinventing many wheels here, but one reason I’m posting this is so that when I stumble back across wheels others have made later on, I can bring mine out to play as well.

Last week, I had the pleasure of embarking on a spontaneous research discussion with several undergraduate students in our lab (and oh my gosh, everyone, it’s really fun to sign about research because of how much you can play with space*). For context: our lab has historically built things, and publishing papers on the things we build is a fairly new concept. The students are working (some for the first time) on poster abstracts for an upcoming conference, and one had asked for feedback on their draft. I realized it was a teaching moment, rounded up everyone who wasn’t busy, and proceeded to do a group-run workshopping of the first student’s abstract (which, by the way, is a clever museum access system that I’m pretty eager to see written up).

In this particular moment, I realized that the biggest gains were to be had in helping the student realize what they had already said. There were some great ideas in the first draft — in fact, most of what they needed was already there. The trouble was that it was all jumbled up; context trailed into conclusion with a detour through a sentence full of technology-related acronyms. So I made a quick reference to Common Things Your Abstract Might Be Trying To Do, a.k.a. The CAT Lab Abstract Sorting Hat (below) and we went sentence by sentence through the current draft, sorting each bit into its respective house(s) — I mean, uh… sections.

I apologize for the Harry Potter metaphor, but it could have been worse. (Contextpuff! Problemdor!) Examples are paraphrases from our discussion today — I’ve removed details so as to not ruin surprises for their eventual publication.

The CAT Lab Abstract Sorting Hat, Version 0.1

1. Context. What is the situation you are designing within? Start with things your audience will recognize. (Example from today: Museums often include audio-recorded or live spoken-language tours to teach visitors about the history and context of the exhibits they are viewing.)

2. Problem. What is the challenge you are addressing? Be conscious of how you frame the problem, especially if you are working with access-related technologies. (Example: Deaf and hard-of-hearing (DHH) visitors to museums don’t have the same level of access to spoken/audio-recorded tour information. In our framing, it is important that the problem is not that we are DHH, it is that museums have not considered visual access and have therefore left out DHH audiences.)

3. Prior work. What have you and others done in the past to address the problem? What work are you building upon?

4. New work. What is the new contribution you are describing in this specific publication? (Example: our lab has built device A to address problem B; in this paper we describe the new features we just added, namely C and D.)

5. Technical details (optional). if you are utilizing specific technologies that you would like to note, they go after #4 (which describes what the solution does). In the context of a lab full of excited engineering/CS undergrads, I added a note that oftentimes, these details are not important for the abstract compared to what we might usually be inclined to put down.

6. Implications / “so what” / (ASL:for-for)? Why is your work important – what could it change? What would happen if the problem you described in #2 was solved? Be as specific as possible (“allow native ASL users to study STEM topics using their native language” is better than “helps DHH students learn”).

End of the CAT Lab Abstract Sorting Hat, Version 0.1

It’s wonderful to watch students just… be around the lab, working on things. As someone who didn’t get to grow up in this (American Deaf) culture or with this language (ASL), I’m learning a lot from them in just… how to… be. People. Who sign. About engineering. I wonder if this is how new Olin faculty feel, landing as teachers inside a culture they were never students within.

*regarding playing with space to discuss research: even if we weren’t getting into the actual content of our papers, the papers themselves lent themselves to spatial setup. The relative lengths and positions of paragraphs and sections (with accompanying facial expressions denoting emotions about various parts), cutting and pasting and twiddling phrasings and words – I’ve thought about editing spatially even before I learned to sign, but watching students (who are more fluent signers than I am) basically collaboratively editing a document in their shared imagination in mid-air — man, that was pretty cool.


Lab research setup email: creating Zotero accounts


I like sharing reusable text I come up with. In this case, part of setting up research infrastructure for my lab includes getting everyone into a citation management system and giving us a way to share reading notes. I don’t have anything against EndNote or Mendeley (and may someday switch, if massive advantages become apparent), but this email is written for Zotero.

Hi, folks – you should have invitations to create Zotero accounts. The only action item you need to take now is following that link and creating an account, which should take a few minutes. You can safely ignore the rest of this email right now, but read on if you want more information/context.

Zotero is a reference management system. It’s useful for keeping track of reading notes and bibliographic information (which we’ll need for our references section every time we write a paper). Other systems include Endnote and Mendeley; there’s no huge advantage of one over the other, but Zotero is (1) familiar to the librarians at RIT and (2) something I already have a lot of notes in, so I’m starting us out with this.

Zotero is free and open source. When you create an account, you’ll probably be prompted to download and install the Zotero browser extension. I prefer to use the standalone desktop software, but that’s your choice.

Right now, the group library is empty. That will change as I begin writing the literature reviews for our ASEE papers. Feel free to add any citations of your own, and/or to start your own individual Zotero libraries (mine is huge; as I find things in it that may be useful to CAT as a whole, I will copy them into the group folder as well).

I have my own conventions for taking notes in Zotero in ways that are easy to write papers from later  – if you really want to, you can read about it here (http://blog.melchua.com/2015/01/28/how-i-use-zotero-to-take-research-reading-notes/) but I am also happy to show you my system any time we sit down to work together.

Here’s to better research infrastructure!

–Mel


Things that have made me happy lately: qual methods companion resource in ASL, my upcoming review of wake-up systems


These are random things that have made me happy today.

The first is that there is an ASL companion to a qualitative research methods textbook (focused on education and psychology, to boot!) I am already fascinated by the design and translation choices they have made in figuring out what it even means to have an ASL qual methods textbook… how multiple signers in the introduction switch between freezing in black and white when it’s not their turn, and becoming full-color and in-motion when it is, so your eye immediately knows who it’s following. How they’ve translated the phrase “chapter author” not as [chapter write-person], but rather as [chapter sign-person] — “they who have signed the chapters” rather than “they who have written down text for the chapters,” because the “text” is in ASL. These little subtle things that tell you that… yes, this is another culture; this is a different world. (Or in my framing: this is an alternate ontology.

Second is that I am giving my portion of a technology review lecture series (1) on ASL and (2) with a fairly decent dose of snarky humor. My topic? “Wake-up systems for DHH sleepers.” I plan to cover…

  • Cheap Hacks for People With Residual Hearing: makeshift and wholly mechanical scoop and rattle amplifiers for phones (put them on big hard hollow things or in cones made of hard materials… like hotel ice buckets!) Also, reasons why these setups may not be the greatest for smartphone users and/or profoundly deaf deep sleepers like myself.
  • Sonic Alert’s Sonic Boom, which emits ear-splitting shrieks at modifiable frequencies, flashes lights (or rather, intermittently turns on and off power to an electrical outlet embedded into its side), and rumbles a bed-shaker. (And, in high school when I had it close to my CRT monitor, it degaussed my monitor. Anyone want to check out a cute little EMP source?) Also, a brief overview of the sleep cycle, and how this device, while highly effective at actually waking one up, is terrible for waking one up pleasantly.
  • Philips Wake-Up Light: awesome, but expensive-ish, and… let’s talk about the usability of the physical design, shall we? (And the choice of bird sounds as the wake-up recording, which… to me, are setting options of “silence,” “other silence,” and “more different silence.”)
  • Philips Hue system as a cheaper and more hack-ish way to replicate some of the functionality of the wake-up light

Gotta work on my content, draft, translate, and rehearse this. It’ll be fun.


Thanksgiving recipe rap: Alexander Hamilton


For context: my family’s Thanksgiving tradition is that we do it potluck-style, and everyone prepares a dish matching some kind of theme, often a goofy one. For instance, last year’s theme was “Literature,” so we had Watership Down salad, Oliver Twist “more” soup, etc. This year’s theme was “It’s a (w)rap,” which covered either food encased in other food and/or food related to rap music. 

Also for context: I learned that there’s a dish called Chicken Alexander, which is basically Chicken a la King with a mashed potato crust, and immediately thought “oh, I could use pork instead, and thennnn…”

Also for context: play this music in the background (will be obvious from the title even if you don’t listen) – and you may be able to replicate my performance introducing this dish at the Thanksgiving table.

how does some carrots, onions, chardonnay and cream
of mushroom soup that get dropped into the middle of a slow boiled
pot of shredded kale ribbons to add a little green
match up with our Thanksgiving theme?

this ten-dollar bottle of supermarket wine will add a lot o’
flavor into the pot, that little alcoholic mottle
that goes full throttle to hit the spot, it’ll
be the efficient cause of the deliciousness, to ref’rence Aristotle

and every day when I was slaving away over my papers
trying to hack the tenure track with my researcher labors,
inside, I really needed some distractionary capers
from the day to day press of all my scholarship endeavours

then this rap came, and the recipe came, and I had it
since these parody songs have been a childhood habit
and a day or two off writing isn’t really all that bad,
it became a plain diversion from the pain of my whole train

of thought – I have to do my edits, really should abstain, man
planning out a recipe around a rap is vain, man
focus on your work, not on the Thanksgiving main, man
but I’m sorry, my left brain
it’s just insane, man

Alexander Hamilton
This dish is Alexander Hamilton
I planned this recipe around that pun
So just you wait, just you wait


Reading effectively: how my practice evolved from engineer to scholar


I came across Reading Effectively via a tweet by Sara Hendren (thanks, Sara!) and it spurred me to reflect on how I read as a scholar, how I have learned to read, and how I want to continue developing these skills both for myself and those I mentor/teach. Specifically, I’m writing from the perspective of someone who was trained in a STEM field (electrical/computer engineering) and then worked in tech before returning to academia and being plunged into the world of theory.

I thought I mostly knew how to read “theory” when I started grad school. After all, I would read non-technical books (!!!) from fields like anthropology (!!! look at how cross-disciplinary I’ve become!!!) and they would kinda make sense, you know? Maybe it was slow and hard and I had to look up some words on Wikipedia, but… fundamentally, I thought I kinda got it. Wasn’t hard. I mean, I was an engineer. I just… needed to read more stuff.

Now I am pretty sure I don’t know how to “read theory,” and am fumbling my way through complex webs of thought that are larger than what my brain will ever be able to hold. It’s fun. It’s grueling. I love it. And my reading as a scholar is very different from the way I learned to read as an engineer.

There are a lot of similarities. In engineering school (and then at work), I learned that sometimes, reading was slow and hard. Whether it was code, documentation, a technical paper, or a detailed email, sometimes you had to pick through and parse, and backtrace, and look up things that were being referred to (what was that code library for, again?) and sometimes the history of things was important because this part was compatible with an earlier version of thing X, not the current version. I learned that speed was not a metric of success; I learned that sometimes, wrestling with my reading yielded fruit I’d never seen on the first skim through it. I learned to keep an eye out for boundaries and limitations (

I learned that speed was not a metric of success; I learned that sometimes, wrestling with my reading yielded fruit I’d never seen on the first skim through it. I learned to keep an eye out for boundaries and limitations; this device was only tested up to such and such a speed, this wiki page was last updated N months ago and surely the codebase has evolved since then… nobody has done A, or B, or C, and so I could contribute there. These are all useful patterns I continue to employ as a junior scholar.

However, my reading as an engineer (that’s what I’m going to call it for now, since that’s what I was at the time, although this isn’t how all engineers read nor how engineers have to read) is, at its core, different from the reading I do as an engineer-who-is-a-scholar… and specifically, who has spent time in more social-science and arts and humanities environments and methodologies and discourses, and who is super aware that she is still learning it as a new and unfamiliar world.

Here’s the difference.

As an engineer, I was working hard to figure out what the text meant, and this was a task that I could do. Because there was a meaning — singular — to be extracted. The author had thought of a math proof, noted it carefully down, published it, and now I had that in my hands and my task was to… unzip the file, so to speak — unpack and install the archive of their thought into my brain, perhaps adapt it slightly to its new environment. And later I could build upon it. But as a reader, my task was fundamentally to understand the thing (singular) that the author said. And oh, maybe that thing they said had been built-upon later, superseded, whatever… but if so, it would be a fairly simple historical march of continuous improvement towards… uh… I don’t know. Betterness!

Now, as a junior scholar… I’m still working hard, but I’m now trying to get glimpses of what the text could mean. To whom, and how, and why… and where, and how it could mean different things, and which meanings I wanted to pull out and relate to, and how things I did and said and wrote could open different possibilities for what the text could mean. Writing is part of reading. Discussing is part of reading. Breaking from the page in frustrated exhaustion, slumping into a friend’s couch, and having a random thought strike me differently while staring at their bookshelf over dinner… also part of reading.

This is not a finite task; this is not a task that I can do in the sense of completing it and being-done — but it is a practice that I can engage in, and it is a practice that mandates socialization. In my engineering-model of reading, reading-with-others was a means to sometimes get to the same end point (understanding the author) faster, but if I were smart enough and had enough time, I could do exactly the same thing alone. In my current junior-scholar-model of reading, reading-with-others is fundamentally different from reading alone. My interactions with others become part of the text we work with (yes, yes, you can make jokes about this); any “end points” I come up with are decisions I’ve made (I will stop because we’re going to submit this paper; we will stop when the semester ends etc.) — and they’re less periods than semicolons, pauses that can be picked up again at any time in the future, whether we do or not.

The article that spurred these thoughts seems to speak to the latter kind of reading, seems to assume that — well, yes, that is the kind you’re doing. But for some fields, that’s not how scholarly reading works. That’s not our practice. Maybe for good reasons, too (if the end goal is “make the device run, NOW,” you may not need to exhume the racial context of the time period during which the documentation was written in order to accomplish it). To someone with a different disciplinary practice of reading, this article feels really, really weird. And I’ve had to learn my way into it, and I will constantly be learning my way into it — I’m old enough now that new things I encounter will never become my “native” ways of being; even if the new ways become more dominant, I’ll always have had a practice (or absence thereof) for that thing before.

And the people I will teach and mentor into scholarly reading will, by and large, also be non-natives — just because of age and experience, since I teach college students, faculty… not tiny ones. And so I will be conscious of that, when I teach people how to read, and as I keep on working on my own practice. I’m not from here; I can’t assume I know; don’t get complacent, stay awake.


Playing with O*NET visualizations for degree program proposals


Edit: Found it! Paul Ingemi located the corresponding “this is for programmers!” website, which I have no idea how I overlooked. But onetcenter.org has everything for download in different db formats. Yesssss.

I’m working on a small project involving how to propose new STEM-related degree programs, and wanted to jot down this resource and think-aloud about my attempts to understand how I might use it.

The Department of Labor has a website front-end for O*NET, a database with information about jobs. Job outlooks (is this field expected to grow, etc.?) are one of the pieces of information, number of people in that industry, and other stats I expected to see — but then others I hadn’t thought of, such as “which skills does this job require?”

That last bit allows comparisons of easy lateral moves — if you’re trained in career A, and want to switch, what professions are most similar (but may not be in an obviously similar industry)? For instance, it seems logical to me that a truck driver would also probably be a good train operator, but I wouldn’t have thought they would be using skills similar to an explosives worker… but okay, yes, big risky pieces of equipment that you have to operate… yes.

This NYT article on career-switching has interactive visualizations that play with the O*NET data. I can’t immediately figure out how — there’s no source code or obvious API on the O*NET side. I wonder how easy it would be to hook to the database, or even scrape it if need be (but that seems silly; there ought to be an interface — at the same time, that doesn’t mean there actually is one). I wonder how we might use this information to think about how to choose new degree programs to start.

For instance, we could look at popular degree programs that cannot possibly accept all of the students that apply, and find skill-adjacent careers to try and expand the number of things students with similar interests can go into (if expanding existing degree programs is not an option). We could screen potential new programs not only by job growth outlook, but by lateral move possibilities – what sorts of degrees will give students the widest range of options if they want to do something different post-graduation, or make it easier to switch majors before graduation? (Engineering degrees are notoriously bad for switching-into from another major, since they require so many specific prerequisite course chains.)

So there’s that one question on my mind — what might we do with this data if we could play with it? And then there’s the second question, which is: how might we (on a technical level) play with it?

The O*NET website doesn’t have a listed API that I can find. I cannot figure out how to directly query the data, short of going all Ryan Mitchell on it and scraping the heck out of a lot of pages. This seems extremely silly. Maybe I’m missing something. But when Sebastian and I looked (thanks for sanity-checking me, Sebastian!) there wasn’t any indication how the NYT piece pulled data from the O*NET database to make the visualizations. We suspect it may be a case of “we threw programmer-hours at the problem” as opposed to “this dataset was easy to manipulate.”

So as to not wander down rabbit holes, I’ve messaged the article authors asking if there’s an easy way to learn more about their methodology. And then… onwards, to working on degree program proposals. Ah, research life.