普通视图

Received before yesterday

An Adapter Adapter

2026年3月23日 23:43

Over the weekend, one of the amazing student Technologists, Link did a clean and reorganizing of the resin 3D printer station. The printer gives off some nasty fumes, so she was able to procure an air purifier set up just for such printers. Unfortunately, the model available doesn’t directly connect with our Prusa SL1S. Link put the air filter in place, but had to resort to duct tape to get it ti connect to the resin printer. It didn’t work.

So when I came in this morning and saw the need for an adapter to the adapter, I knew what I was going to do today!

I spent some time thinking about the best options. An insert with magnets? But how does the original adapter stay put on the new adapter?

Well, there are screw holes, how about using them? Yep, that’s the ticket. Basically replicate the bottom of the original adapter so it can screw to the new, then add a whole bunch of magnets!

Alt text

And it worked on the first try! I had to double up the magnets in order to make it strong enough to stay on, and the gasket printed in TPU could be a little bit thicker. But it was a great success!

Alt text

The models are available on Printables.com for download and 3D printing.

Gear Train Assemble!

2026年3月19日 19:01

seven versions of the holder so far

On the heels of the knowledge gained from the last post figuring out the gear train numbers, I set out to model the gears and a holder.

And immediately I was confronted with an issue with my calculations.

The Problem

At the end of all my learning and calculating, I decided:

It looks like 36mm (servo) —> 12mm|36mm —> 12mm (pinion) 
has smaller gears and gives good enough range.

One thing I forgot to consider is the length of the servo horn that is used to connect the servo to the gear. I could do without it, but trying to design and print such a small toothed hole has issues. I have seen others try and filament 3D printing does not provide fine enough detail to mesh well with the servo gear. So using the supplied horn attachment makes things much easier.

The problem, is that the horn is about 22mm in length. If my gear is only 36mm in diameter, then the horn would stick out into the gear’s teeth!

Gear is too small!

Another sidetrack bump I had to overcome was the getting the dimensions of the servo horn. The dimensions I could fine online were unsatisfactory. So I measured one myself!

SG90 servo horn

And went ahead and 3D modeled it and put the 3D model and diagram files up on printables.com for anyone to use.

With all of that info, I can then recalculate the gear train dimensions so it fits with the servo horn.

The Correct Gear Train

I played around with different settings, but it seemed the best option (that being the smallest size for the servo and large combo gears) called for a 46mm servo gear → 20mm 46mm combo gear → 20mm pinion.
Servo motor → 46
              ↓
             20 (same shaft as) 46
                                ↓
                               20 (pinion)

Sidetracked Again!

The first day of modeling, I decided to jump the Fusion 360 train and try onshape.com. It’s a web based 3D modeling and CAD tool. It has been around since 2015, and is gaining ad time lately in many of the YouTube.com videos I see, so I thought I’d give it a try. I was prepared for some learning curves and to spend some time learning a new system, but two things got me to throw in the towel after a full day of working with it; 1) I couldn’t figure out how to do something pretty simple that would take 2 minutes in Fusion 360, 2) I didn’t care for the interface; it felt too unprofessional. If TinkerCad.com is the elementary school version of CAD, it looked like Onshape.com was the 9th grade version. I did love that it was browser based. And making double helical gears was a breeze! There’s a handy built in menu for all kinds of gears. Fusion 360 on the other hand is big L in gear making. You have to import 3rd-party scripts and I can’t get any of the fancy gear scripts to work.

Like many things, it was the fact that I could get things done much faster with the tool I already knew, and I was accustomed to the interface that led me back to Fusion 360.

Making the Gear Train

I had previous attempts at designing the gear train, but I decided to start from scratch since Fusion 360 doesn’t have an easy way to just change the size of gears when using the gear script plugin thing.

Servo Gear

So, first I designed the servo gear. Pretty easy to create a 46 tooth gear with the gear script plugin thing.

servo gear with inset for servo horn

I designed a cut out, or inset, for the servo horn to fit inside. This is the easiest way to attach the gear to the servo. 3D printing these gears with filament would not have enough resolution to print the fine teeth needed to interface with the tiny default gear on the servo shaft. Much easier to use the included horn.

Combo Gear

The combo gear was pretty easy, too. Just make another 46 Tooth gear, then make a 20 Tooth gear and stack them on top of each other.

combo gear

I set the diameter of the hole through the gear at 4.2mm. That’s big enough for a M4 bolt to go through, with just enough tolerance to allow the gear to spin but not wobble.

Pinion Gear

Another very simple gear to model. There’s nothing special about this, just a 20 tooth gear with a 4.2mm diameter hole.

pinion gear

Rack

The rack is pretty straight forward. I created a 20 tooth gear, then used one of those teeth to copy down the length of the rack.

pinion gear

pinion gear

Gear Holder

This was a little bit tricker. The gears were all prototyped in one go. The first print was great. This part took 7 tries so far.

seven versions of the holder so far

I started by creating a new Assembly in Fusion. Then adding in the gears and aligning them as needed. I went with a stacked approach so as to keep the footprint as small as possible. I had previously modeled the servo motor, so I was able to add that in as well.

It was tricky to get the servo aligned with the servo gear, and then get each of the gears aligned with the ones the mesh with. In realized that if a part has the sketch turned on, then that shows up in the Assembly file. I used that to create a construction line on the servo gear and put a point where the center of the combo gear should be aligned to. Then I did the same on the combo gear to align the pinion. Then adding the holder, servo motor, and rack.

assembly, color coded

It was a lot of back and forth between the designs for the parts and the assembly to align everything correctly. But in the end I think it lines up well.

Spacers

After the first version, I realized that the gears needed spacers to keep them in place. The holder is wider than the gears. So modeling and printing a couple of spacers is pretty easy.

spacer

Somewhat Working

I connected everything up, bolted in the gears, and plugged it in. And it works… mostly.

As the video shows, the gears work, somewhat. There is a bit of jittering, which may be due to the code just rotating the gears back and forth. A more normal behavior would be moving from one angle to the next and stopping there. The servo is also not moving at a full 180°. More like 100°. This is only about 111mm of travel, not the 150mm we’re hoping for. It might be time to consider better quality servos. Perhaps some that move 270°.

It is also a pain to swap the servo motor. Perhaps a redesign is in order.


Missed the first two posts?

Funding provided through a generous grant from UVA Arts Council. Alt text

Jump on the Gear Train! - Critical Making 2025-2026 - Part 2

2026年2月27日 20:32

This week I started figuring out the gear train and rack and pinion needed to move the states. I have tried in the past to get AI to do this for me, but the results from ChatGPT and Copilot are all over the place and offer varying results every time I ask. I decided to use AI to learn the math instead of trying to get it to figure it out for me. Instead, I’m learning the math behind the problem to work it out myself.

Be forewarned, there is lots of math!

math?!?

TLDR;

What helped immensely was GearGenerator.com

And a spreadsheet that AI generated to calculate the travel distance of a rack based on the pinion diameter and number of rotations.

With help from GearGenerator.com I created a gear train which starts with a 36mm gear attached to a servo motor that meshes with a 12mm gear which is on the same axle (or combined) with a 36mm gear that then meshes with a 12mm pinion.

Input Value Units / Notes
Servo Gear Diameter 36 mm
Servo Gear Rotations 0.5 rev (revolutions)
     
Combo Gear Small Diameter 12 mm
Combo Gear Small Rotations 1.5 rev
Combo Gear Large Diameter 36 mm
Combo Gear Large Rotations 1.5 rev
     
Pinion Diameter 12 mm
Pinion Rotations 4.5 rev
     
Output Formula Result
Rack Travel per Rotation 37.69911184 mm
Total Rack Travel 169.6460033 mm

But how did I get this this answer?

Well, let me take you on a journey to how I figured this out and understood the problem.

What am I trying to do?

Each state will move up and down based on the data given. Prof. Rich Ross and I want this to be a pretty dramatic difference between the lowest and highest states, so we decided on 150mm of movement. After much deliberation and looking at various options, Yashu and I decided that a rack and pinion would be the easiest way to accomplish the goal. What is a rack and pinion? It’s simply a gear that moves a bar with gear teeth. It turns a rotational movement into a linear movement. The round gear is the pinion, the bar with teeth is the rack. )

A rack and pinion, a large circular gear moving a long bar with teeth

We figured the servo can rotate the pinion and move the rack attached to the bottom of the state up and down. (See last week’s post with a video of the test case.)

First Gear

The first question we needed to answer was; How far does the rack travel based on the size of the pinion?

The formula to figure this out is

\( T = Dπ \)

T is the rack travel distance, D is the diameter of the pinion, π is yummy and 3.14159265359…

It’s basic middle school geometry. The travel distance is just the circumference of the gear.

But our servo motor only goes 180-degrees, or half a rotation, or half the circumference. So we’ll have to keep that into consideration.

\( T = {Dπ \over 2} \)

The smallest size gear we want to use is probably 12mm. I just pulled that number out of the air (but actually, we’ll use it because I already know it works within all the parameters and constraints for the project 😁 ).

A pinion gear with a diameter of 12mm will cause a rack to travel \( T = 12π = 37.699mm \) But since our servo can only do a half rotation, the rack travel length is \( T = {12π \over 2} = 18.85mm \). I want the rack to travel at least 150mm. So a 12mm gear is not going to work.

In order to get the rack to travel 150mm from a single gear, we can calculate that

\( T = {Dπ \over 2} \)

\( {2T \over π} = D \)

\( {2(150) \over π} = 95.493mm \)

We would need a 95.5mm diameter pinion!

The footprint of the smallest state is about 45mm square. So everything has to fit within that area. So the largest a gear can be is about 40mm. We’ll need a different way to do this.

One option is to use multiple gears. We can use multiple small gears to create the same effect as one large gear. How does that work?

Second Gear

Well, if we just have two gears and one is smaller than the other, then if we turn the small gear one full rotation, the bigger gear will turn less than one full rotation. If the bigger gear is twice the size of the smaller gear, then for every 2 turns of the small gear, the big gear will turn once.

The blue, smaller gear is the one moving, or driving the larger gear

small turning large

The opposite is true, too. If the big gear rotates one full revolution, the small gear revolves twice.

large gear turning a small gear

Large turning small

The ratio between the sizes of the gears is called the gear ratio. The gear ratio is derived from the diameter of the gear doing the revolving divided by the diameter of the gear connected to the moving gear. We can call these the driving gear (the one attached to a servo or some other source that generated the movement) and the driven gear. So we get the formula:

Ratio (R) = Diameter (D) of driven gear (n) / Diameter (D) of driving gear (g)

\( R = {Dn \over Dg} \)

If the ratio is greater than 1, then the output is a slower turning gear, a reduction in speed.

If the ratio is smaller than 1, then the output is a faster turning gear, an amplification of speed.

Start with a smaller wheel, the bigger wheel turns slower. Start with a bigger wheel, the smaller wheel turns faster.

We also write the ratio like this R = Dn:Dg

OK. Next, how do we figure out the gear ratios for the gear train, and how many do we need?

Let’s take two gears, one is 36mm in diameter and the other is 12mm.

If the 12mm gear is the driving gear (it is connected to the servo), then the ratio is \( R = {36 \over 12} = {3 \over 1} \) or 3:1. The ratio is greater than 1, so the output is a slower turning gear.

One way to look at it is to read the ratio from left to right. A bigger number is faster than a smaller number. R = 3:1. 3 to 1. This is a decrease. From speed 3 to speed 1. Slower.

But if the driving gear is 36mm, then the ratio is \( R = {12 \over 36} = {1 \over 3} \) or 1:3, the output is a faster turning gear.

Read from left to right. 1 to 3, is an increase. From speed 1 to speed 3. Faster.

If we stick with a 12mm pinion, how many times does it need to revolve in order move a rack 150mm?

The circumference of a 12mm pinion is

\( C = Dπ \)

\( C = 12π = 37.699mm \)

so

\( {150mm \over 37.699mm} = 3.9789 \) revolutions

A 12mm pinion needs to rotate about 4 times in order to move a rack 150mm.

So if we have a second gear turning the 12mm pinion, how big does it need to be. Recall that the servo gear will only be able to rotate half of a rotation. The gear ratio, then, needs to be 0.5:4. Half a rotation to 4.

\( {12 \over x} = {0.5 \over 4} \)

Doing some cross multiply,

\( 12(4) = 0.5x \)

\( {48 \over 0.5} = x \)

and we get that x = 96. Whelp. Back to a 96mm gear. This is because the servo gear only rotates halfway.

Third Gear

So, I ask myself, “Self, if you know the pinion size and how many rotations it needs to complete, how do you calculate the other gears in the train if you don’t know exactly what sizes and how many are needed?”

I replied, “You know, that’s something that I don’t know.”

Well, I asked Copilot, too. (Copilot took into account previous conversations where I told it the gear ratio was 0.5:4 and an earlier example using 36mm and 12mm gears. And it uses gear Teeth instead of Diameter, but these are the same thing.):

Copilot said:

Great question —- this is the heart of gear‑train design. When you know:

  • the pinion diameter (or teeth)
  • the pinion rotations required

…but you don’t yet know:

  • how many gears
  • what sizes
  • or which ratios

…you can still design the entire gear train systematically using a step‑by‑step math process. Below is the cleanest and most universal method mechanical engineers use.

✅ Step 1 — Convert rack travel to pinion rotations (if needed)

If you already know the pinion must turn N rotations, skip this. If you only know the travel distance:

\( Pinion Rotations = {Rack Travel \over πD} \)

✅ Step 2 — Determine the required gear‑train ratio

This is the most important step. You need to know:

  • How many rotations the motor (input) produces

vs.

  • How many rotations the pinion (output) must make

\( R_{total} = { \text{Pinion RPM or Rotations} \over \text{Motor RPM or Rotations}} \)

Example:

  • Servo rotates 0.5 turns
  • Pinion must rotate 4.5 turns

\( R_{total} = {4.5 \over 0.5} = 9 \)

So the gear train must create a 9× speed increase (or 1:9 reduction, depending on convention).

✅ Step 3 — Factor the total ratio into small ratios

Gear trains are built by splitting a large ratio into smaller multiply‑able pieces. For example, if your target is:

\( R_{total} = 9 \)

Then possible factorizations are:

  • 3 × 3
  • 1.5 × 6
  • 1.5 × 1.5 × 4
  • 2 × 4.5
  • 1.2 × 1.25 × 3 × 2
  • (36→12) × (36→12) ← your earlier example

You can pick any combination of small ratios that multiplies to your total.

✅ Step 4 — Assign tooth counts to each ratio

Each stage ratio is:

\( R = {T_{driven} \over T_{driver}} \)

For example, suppose you choose two stages:

\( R_{1} = 3 \), \( R_{2} = 3 \)

You now choose tooth counts that satisfy each:

Stage 1: ratio = 3

Examples:

  • 12 driving 36
  • 10 driving 30
  • 16 driving 48

Stage 2: ratio = 3

Same options.

A compound gear (two gears on one shaft) lets you chain them:

(motor) 36
        | (ratio of 3)
        ↓
       [12 same shaft as 36]
                          | (ratio of 3)
                          ↓
                (pinion) 12

Ratios multiply:

\( 3×3=9 \)

✅ Step 5 — Check physical constraints

When selecting gear sizes, check:

  • Gear diameters fit in available space
  • Teeth counts match a common module or DP
  • Shaft spacing is feasible
  • 3D printing tolerances allow proper meshing
  • Required torque is acceptable
  • Compound gears are not too small or too fragile

If something doesn’t fit, adjust tooth counts but keep ratio the same.

✅ Step 6 — Iterate until a valid mechanical layout exists

This is normal: you will often try 3–6 combinations until the gear spacing, shafts, and reductions all work.

🧮 A Worked Example (General Method)

Suppose:

  • You want 5 pinion rotations
  • Input shaft makes 1 rotation
  • Total ratio required:

\( R_{total} = 5 \)

Factor it:

  • 5 = 5
  • 5 = 2.5 × 2
  • 5 = 1.25 × 4
  • 5 = 1.666 × 3

Pick: 2.5 × 2

Assign tooth counts:

  • Stage 1: 12 → 30 (ratio = \(30 \over 12 \) = 30:12 = 2.5)
  • Stage 2: 15 → 30 (ratio = \(30 \over 15 \) = 30:15 = 2.0)

Total:

\( 2.5 × 2 = 5 \)

Build it as a compound:

(input shaft) 30T
              ↓
              12T -- same shaft -- 15T
                                    ↓
                          (pinion) 30T

Pinion rotates 5× per 1 input rotation.

🎯 The Key Insight

You don’t need to know the gear sizes up front. You only need to know the total ratio, and then you can:

  1. Factor the ratio into small ratios
  2. Assign teeth counts that match each small ratio
  3. Assemble them into a compound gear train
  4. Adjust until it fits mechanically

This process is how all engineered gearboxes are designed.

Fourth Gear

OK. That’s cool. Now to ask Copilot to figure it all out for me.

“Copilot, walk me through each step of how to calculate a gear train to drive a pinion 4 rotation with a servo motor generating 0.5 rotations and the largest a gear can be is 40mm, and using the smallest number of gears possible, and the gears should be easily 3D printed.”

Copilot said:

Reasoning completed in 3 steps

Absolutely-—let’s design a compact gear train that makes a pinion turn 4 rotations when your servo only turns 0.5 rotations, with the constraint that no gear may exceed 40 mm diameter, using the fewest gears possible and keeping everything easy to 3D print.

🎯 What we need (in plain math)

  • Input (servo): 0.5 rotations
  • Output (pinion): 4 rotations
  • Required speed increase:

\( S_{total} = {\text{pinion rotations} \over \text{servo rotations} = {4 \over 0.5} = 8 \)

So the gear train must provide an 8× speed increase (equivalently, a 1:8 reduction in the “driven/driver” convention).

  • Constraint: largest gear ≤ 40 mm diameter.
  • Goal: Fewest gears (i.e., 2 stages / 4 gears total with one compound shaft).

✅ We’ll target a two‑stage compound gear train (4 gears total). If we can’t meet printability constraints, I’ll give a 3‑stage fallback.

🔧 Design conventions (for easy 3D printing)

  • Use equal gear module (e.g., module m = 1 mm/tooth) so:

\( \text{Pitch diameter (mm)} ≈ m × \text{tooth count} \)

With m=1, a 40‑tooth gear ≈ 40 mm diameter—- perfect for your 40 mm limit.

  • Common printable tooth counts (no special profile shift): 12, 15, 16, 18, 20, 24, 30, 36, 40.
  • Pressure angle: 20° (typical for printable involute gears).
  • Try to avoid very small tooth counts (<12) to reduce undercut and fragility.

🧮 Step‑by‑step method

Step 1 — Decompose the total ratio into stage ratios

We need:

\( S_{total} = S_{1} × S_{2} = 8 \)

We’ll look for two reasonable stage increases (each <4×) that multiply to 8.

A convenient split is 3.333… × 2.4 ≈ 8.

Step 2 — Map stage ratios to tooth (or diameter) ratios

Speed increase for a stage (driver → driven) is:

\( S = {D_{driver} \over D_{driven}} = {T_{driver} \over T_{driven}} \)

(Assuming same module.)

So we want (example picks):

  • Stage 1 \( S_{1} ≈ 3.333 \): 40T → 12T (\( 40 \over 12 \) = 3.333…)
  • Stage 2 \( S_{2} = 2.4 \): 36T → 15T (\( 36 \over 15 \) = 2.4)

Total:

\( S_{total} = {40 \over 12} × {36 \over 15} = {10 \over 3} × {12 \over 5} = {120 \over 15} = 8 \)

Bingo.

Step 3 — Lay out the gear train (compound shaft)

[(A)40T Servo]  
    |
  meshes                        Stage 1 (40→12)                      
    ↓ 
[(B)12T same shaft as (C)36T]  
                        |
                      meshes    Stage 2 (36→15)
                        ↓
                 [(D)15T Pinion]
  • (A) is connected to the servo motor.
  • (B) and (C) are rigidly fixed on the same shaft (compound).
  • The pinion is gear (D) = 15T in this design.

Step 4 — Verify motion requirement

Servo turns 0.5 rev → pinion turns:

\( 0.5 × 8 = 4\text{rev} \)

Meets the spec. ✅

Step 5 — Verify size constraints (≤40 mm)

With m = 1 mm/tooth:

  • 40T → ~40 mm
  • 36T → ~36 mm
  • 15T → ~15 mm
  • 12T → ~12 mm

All ≤ 40 mm. ✅

Step 6 — Check printability & robustness

  • Smallest gear is 12T—printable in PLA/PETG with 20° PA; 15T pinion is sturdier and meshes well.
  • Keep face width ~6–10 mm for strength (depends on load).
  • Add 0.1–0.2 mm backlash target (or scale tooth thickness down ~1–2%) to compensate for printer tolerances.
  • Use fillets at hub/arm junctions; ensure set‑screw hub or D‑shaft interface.

✅ Minimal‑gear solution (recommended)

Two stages / four gears (one compound shaft):

  • Stage 1: 40T → 12T (3.333× speed increase)
  • Stage 2: 36T → 15T (2.4× speed increase)
  • Total: 3.333 × 2.4 =
  • Result: Servo 0.5 rev → Pinion 4 rev

This uses just 4 gears and fits the 40 mm cap.

Nice! If we have a 15mm pinion rotating 4 times, that moves the rack

\( T = π × D × 4 \)

\( T = π × 15 × 4 = 188.5mm \)

I plugged these calculations into a spreadsheet (rack_travel_calculator.xlsx) to help me play around with the gear sizes. I wanted something smaller than 40mm.

It looks like 36mm (servo) —> 12mm|36mm —> 12mm (pinion) has smaller gears and gives good enough range.

That’s a 3 × 3 = 9 total ratio. Better than the 8 needed.

12mm pinion rotating 4 times moves a rack

\( T = π × D × 4 \)

\( T = π × 12 × 4 = 150.796mm \)

That’s just perfect, but in a gear train, the pinion actually rotates 4.5 times, so the rack will move 169.646mm. Even more perfect!

gif of gear train at this ratio

Gear train

OK. Now with the math and numbers all figured out, and the some additional tips from Copilot about layout, it’s time to start modeling a gear train!

🧰 Practical layout tips

  • Center distance between meshing gears:

\( c = {m \over 2}(T_{1} + T_{2} ) \)

With m=1, 40T–12T center distance = (1/2)(52) = 26 mm;

36T–15T center distance = (1/2)(51) = 25.5 mm.

  • Maintain parallel shafts and allow axial shimming (washers) to tune backlash.
  • If you’re driving a rack, ensure the final gear module matches the rack’s module (e.g., both m=1).
  • For SG90 servos, print large driver gears with a robust hub and insert brass heat‑set inserts for screws if possible.

Phew! That was a lot! Next week, 3D model the gear train!

Funding provided through a generous grant from UVA Arts Council. Alt text

Read Part 1 - The Beginning

Critical Making Fellowship 2025-2026: Part 1

2026年2月20日 20:54

Introduction

Beginning in 2023, the Makerspace has funded a graduate student, usually in the humanities, to design and complete a physical project that represents or comes from their humanities research. Named the Critical Making Fellowship, the previous projects were Alexa Luborsky’s “Diaspora Poem” (2023), and Holly Zhou’s “Memory Maps” (2024 & 2025). This years Fellowship began as a collaboration with Statistics Professor Rich Ross and Makerspace Manager Ammon Shepherd. Generously funded by an UVA Arts Council Grant, the 2026 project was able to hire Yashu Tang for the Fall 2025 semester to get the process started. Below is the write up of the project and contributions from Yashu.

Project Overview

This project aims to visualize electoral voting patterns in previous presidential elections using an interactive data-sculpture. Each state is represented with a cluster of hexagonal cells equal to the number of electoral votes allocated to the state.

"2012 US Electoral map"

The state-block will have two actions in response to input data:

  1. light up blue or red depending on the party of the winning candidate and
  2. raise or lower itself proportional to the margin of victory.

The data on state-level electoral votes is from UCSB’s American Presidential Project website.

Data

The data has already been scraped from UCSB’s website and contains data on the 1924-2024 elections. They are stored in the election data folder on the shared drive, with a separate .csv file for each election year. Files are named with the convention Election_####, e.g. Election_1968. Years with atypical electoral votes have been noted in the data description document, which can also be found in the election data folder.

The data columns are as follows:

State: State where the data was collected

Total: total votes tallied for the state

Popular_D: Number of popular votes won by the Democratic candidate

Prop_D: Proportion of total votes received by the Democratic candidate

EV_D: Number of electoral votes won by the Democratic candidate

Popular_R: Number of popular votes won by the Republican candidate

Prop_R: Proportion of total votes received by the Republican candidate

EV_R: Number of electoral votes won by the Republican candidate

  • If a 3rd party candidate won electoral votes, the votes will be recorded with similar conventions as above, with “_3rd” as the suffix.

EV_Outcome: Column with electoral vote outcomes. Data is stored with integer values of electoral votes, followed by the party they were cast for, separated by spaces. E.g. 3 D 0 R 0 I, where 3 votes were cast for the Democratic candidate, and 0 for the Republican and Independent/3rd party candidate.

Margin: Margin of victory, calculated using

MOV = (Raw margin of victory) / (Total votes in state)

where the raw margin of victory is the difference in popular votes between the first and second place candidates in the state.

Hardware

The state-blocks will be 3D printed by Ammon at the Makerspace and mounted on a similar 3D printed rack-and-pinion mechanism to achieve the raising and lowering.

The vertical movement will be powered by 180-degree rotation Servo motors. They were chosen because their degree of rotation can be specified in code. This allows for an easy transition from the MOV value in the data into Servo motor directions. The Servo motors will be connected to the Adafruit 16-channel PWM bonnet, and a brief tutorial on connecting and using the bonnet can be found here. For this project, the bonnets will use the 3x4 right angle male headers, so the Servo motors can all interface to the pi.

The light-up portion of the project will be completed with the 5050Neopixels, whose product specifications can be found here. A pdf of the specs will also be in the shared drive. The pin configuration can be found on page 5 of the pdf. When connecting the Neopixel to the bonnets, the signal pin should connect to pin 2 (DIN), the power pin should connect to pin 3 (VDD), and the ground should connect to pin 1 (GND).

  • It should be possible to chain multiple Neopixels by chaining pin 4 (DOUT) to pin 2 (DIN) on another Neopixel, but I haven’t had a chance to test it.

Software

There is some Python code for powering the Servos simultaneously. This is on the Raspberry Pi and should be stored in the “Code” folder. The packages used for powering the Servos and Neopixels must be used in a virtual environment. On Thonny, you can go to “Run”, then “Select interpreter”, then choose the venv that is in the “Code” folder. Not much has been done for the software portion of this project.

February 2026 update

Further consideration about the project led us to expand the vision of the project. Instead of being tied to electoral data, the map will be able to use any two data points to compare states. The LEDs will not be exclusively red or blue, but RGB LEDs will be used to allow a range of colors.

As of February 2026, the hardware side of things has improved a bit. California was chosen for the test case as it is the largest with the most electoral votes. This would test the capability of the inexpensive 180 servo motors to move the 3D printed states.

Originally, it was hoped to use the output of data from the R statistical program to generate the 3D models for printing. The resulting hexagons from this workflow were inconsistent.

Map showing inconsistent hexagon and height

An additional issue, was that the generated file created a map with states at varying heights. We are going to account for this in the hardware by moving the states up and down, so they all need to be the same height.

Modeling each state by hand in Fusion 360 is the solution.

Model of California

Fusion 360 was also used to model the servo holder and a rack and pinion gear set to move the state vertically.

Model of the rack and pinion gear

To test the set up, two pieces of plywood were cut to house the gears and the state. Temporary supports were 3D printed to hold the two pieces of plywood together.

A test case using California can be seen in the video below.

Funding provided through a generous grant from UVA Arts Council. Alt text

Read Part 2 - Jump on the Gear Train

Light Up Your Heart

2026年2月13日 21:30

A great Valentine project to brighten the day for your special someone.

Materials Needed

Step 1 Cut Out Cardboard Shape

Cut a heart shape out of cardboard. You can do any shape you want, though.

Cardboard heart

Step 2 Apply Copper tape

Make a “track” of copper tape around one side of the heart. The rails of the track should not touch. One is for the negative, the other for the positive part of the circuit. Leave a piece unstuck. This will be used for the “button”.

Cardboard heart

Step 3 Poke holes for LEDs

Poke holes in the heart for the LEDs. You can do as many or as few as you want. This one is labeled with - and + to make sure the LEDs are placed correctly.

Cardboard heart

Step 4 Insert LEDs

Push the LED legs through the holes. The short leg is negative ( - ) and the long leg is positive ( + ).

Cardboard heart Cardboard heart

Step 5 Secure LEDs to Copper Tape

Bend the legs of the LEDs so that the negative leg lays flat on the negative rail and the positive leg lays flat on the positive rail. Tape them down so the stay in contact with the rails.

Cardboard heart

Step 6 Make Battery Holder and “Button”

Use cardboard or cardstock to make a ring the size of the battery. The ring should be at least three times as tall as the battery.

Cardboard heart

Fold a piece of cardboard or cardstock to fit like a bridge over the battery ring. The positive ( + ) side of the copper tape will attach to the underside of the bridge to act as a button.

Cardboard heart

Step 7 Secure Battery and Button to Heart

Use Masking tape to secure the battery ring and bridge (button) to the back of the heart. The button should rest on the negative ( - ) rail of copper tape. The positive ( + ) rail of tape should be attached to the bottom of the bridge.

Cardboard heart

Test the LEDs by pressing the button. They should all light up. If not, check to make sure all of the LED legs are touching the correct rail and are firmly taped down.

Step 8 Wind with Yarn

Finally, wide yarn around the heart until all of the cardboard is hidden. Secure the yarn on the back by tying a knot.

Cardboard heart

Press the button on the back to make the LEDs light up!

Cardboard heart

Building Folkloric Futures: A Behind-The-Scenes Look At Designing A Speculative Digital Archive Of Caribbean Storytelling

2026年2月2日 13:00

What would it mean to design a digital archive that doesn’t simply preserve the past, but actively looks both backward and forward—one that helps us think differently about how the past and future speak to each other?

This question kept coming up as I began building Folkloric Futures, an Omeka-based digital archive that brings together Caribbean folklore, literature, visual art, and community storytelling. From the beginning, I knew I didn’t want to create an archive that treated folkloric figures as static artifacts or neatly categorized traditions. These stories are alive. They change depending on who tells them, where they’re told, and why they’re remembered.

Folkloric Futures started as a way to test that idea in practice.

I’m a PhD candidate in English at the University of Virginia, and my academic research focuses on Caribbean literature and speculative storytelling. My dissertation looks at how folkloric Caribbean figures like the soucouyant, douen, jumbie, and moko jumbie move across novels, oral traditions, and visual culture—and how those movements shape ideas about identity, belonging, and survival. But I kept asking myself a bigger question: what would it look like to take those ideas out of a dissertation and build something people could actually explore, use, and contribute to?

This project is my attempt to answer that.


Why folklore—and why speculation?

There’s a line from Martinican writer Patrick Chamoiseau that I return to often: “Their eyes had seen so much that they no longer distinguished between dream and reality” (from Creole Folktales). For me, that line captures what folklore does best. These stories don’t offer neat explanations of the past; they give people ways to live alongside it.

Caribbean folkloric figures are full of contradictions. The soucouyant is frightening, but also powerful—an older woman who sheds her skin and moves through the night as fire. The douen is a child spirit who lingers at the edge of the forest, both vulnerable and unsettling. The moko jumbie towers above the crowd during Carnival, part guardian, part performer. These figures carry history in ways that are felt rather than explained—through fear, humor, warning, and care.

Speculation gives me a way to work with that complexity. Instead of asking, “What is this figure?” speculation asks, “What can this figure do?” What stories does it carry? What futures does it hint at? What happens if we design an archive that allows those meanings to shift rather than settle?


Designing an archive that tells stories

At a basic level, Folkloric Futures is a digital archive built in Omeka. It brings together literary excerpts, oral histories, visual art, and creative reinterpretations of Caribbean folklore. But very quickly, I realized that the hardest part of the project wasn’t collecting materials—it was deciding how the archive should feel.

Most digital archives aim for visual consistency and neutrality. This one couldn’t. These figures don’t belong to a single mood, palette, or structure. So instead of designing one uniform template, I let each figure shape its own page.

The soucouyant’s page uses deep violets and ember-like gradients to suggest heat, night, and movement. The douen’s page is quieter, built around forest greens and shadow, echoing stories of childhood loss and ecological liminality. The moko jumbie’s page is bright and vertical, drawing on the energy of Carnival and the figure’s role as a watcher from above.

These choices aren’t just aesthetic. They’re a way of letting design do some of the storytelling work—guiding how people encounter each figure before they ever read a word.


Metadata, but make it human

Metadata turned out to be one of the most surprising parts of this project.

Folkloric figures don’t stay in one place. Their names change across islands, and their meanings shift between generations. Trying to force them into fixed categories felt like losing what mattered most about them. So instead of treating metadata as a rigid checklist, I started treating it as something closer to a set of prompts.

Instead of asking only where a figure comes from, the archive makes room for multiple origins. It doesn’t settle on a single interpretation, but allows overlapping themes and contradictions to sit side by side. In this way, metadata becomes another storytelling layer—one that reflects how folklore actually moves through the world.


Ethics as something you build in, not add later

Because Folkloric Futures works with living traditions, ethics could not be an afterthought. Early on, I wrote a project charter to guide decisions about collaboration, credit, and care.

That meant committing to a few core ideas:

  • contributors are collaborators, not data sources
  • artists deserve material compensation
  • people should control how their stories are shared
  • accessibility matters, especially for oral and low-bandwidth storytelling

These principles shape everything from submission forms to design choices. Ethics, in this project, isn’t a separate section—it’s part of the infrastructure.


Teaching as part of the archive

Folkloric Futures is also a teaching project. In Spring 2026, I’ll be running a workshop series that invites participants to experiment with archives, oral storytelling, mapping, and creative worldmaking—using both digital tools and low-tech alternatives.

The goal isn’t technical mastery—every workshop includes a low-tech version by design. It’s about helping people see archives as places where stories can be questioned and expanded. In this way, teaching feeds back into the archive, and the archive becomes something shaped by ongoing learning rather than a finished authority.


What building in public has taught me

Working on this project has changed how I think about archives. I’ve learned that design decisions are never neutral, that aesthetics shape interpretation, and that building in public requires patience, iteration, and accountability.

Most of all, it’s reinforced my belief that speculation isn’t escapism. In Caribbean storytelling, imagination is often a survival strategy—a way of carrying history forward without being trapped by it. Folkloric Futures tries to honor that by creating a digital space that doesn’t just preserve stories, but invites people to think with them.

Because an archive, at its best, doesn’t just hold the past. It helps people live with it.

The Slideshow And The Video Essay

作者leo-palma
2026年1月16日 13:00

In my discipline, art history, the slide show is not only an intrinsic part of teaching, but it shaped the discipline’s methods from its inception. Practices through which art historians are taught to understand art – like visual analysis and comparative analysis– rely on one or more reproductions of artworks to be available to students in the classroom. Photographic slides have been used in art history since the early twentieth century. Then why are most art history sideshows so plain? Why, now that technology has advanced, have the conventions of the art history slideshow stayed largely the same?

Outside of academia, video is one of the main ways people consume information. Currently, this is largely through online video. Online educational programs vary greatly in quality and accuracy, but many educated individuals who operate outside of academia have taken to platforms like YouTube to share their knowledge and their analysis on a variety of topics. Some of my personal favourite video essayists hold undergraduate and graduate degrees in philosophy. They often start their videos by addressing a current topical issue or event as a departing point to present different philosophers’ ideas and concepts. While these videos use some academic practices – like citing sources on the top right of the video, or providing a bibliography in the description – their presentation style is definitely not academic. Their videos contain elaborate costumes, makeup and sets; their presentation style is highly emotive: they use humor, plot twists, and personal experiences to make complex topics more approachable. On Youtube, maintaining viewers’ engagement and retention is paramount for the monetisation of a channel. This is often achieved by favouring material that emotionally, rather than just intellectually, engages the viewer. Video essays can be long, sometimes multiple hours. The audience is almost by definition assumed to be a distracted one. Viewers are doing chores, or cooking, or on their commute. To keep them interested and listening, one needs to find ways to not only make the content relevant to them, but create emotional resonance and construct exciting visuals and sound design to highlight important moments. This highly emotional way of presenting differs from academic rigor, expectations of objectivity, and separation between the self and one’s field of study.

While in certain academic fields – largely feminist, queer, black and other minority studies – this requirement has been challenged, it is still an underlying practice in disciplines like art history. Yet, we all spend years of our life studying and researching this material because we love it, because we find it interesting and relevant. So why is it so difficult to communicate passion and enthusiasm in public facing presentations?

I believe there are at least two practices from the YouTube video essay that could translate to the academic presentation: encouraging emotional engagement, and providing variety. In regard to emotion, for example: Where can I script a joke or acknowledge the humor of an aspect of my research? Where can I leave out a conclusion or some information, to surprise my listener with it later? Where can I reenact a moment of my research when I found out something exciting or unexpected? Where can I peel back the curtain a bit on the process of my research, so that the listener feels involved in the narrative I’m presenting, and not just a passive bystander? Importantly, how can I use the tools at my disposal to create these moments of emotional engagement? Where can I hide something on the next slide, as to not give away my findings before I get to them? Where can I include a photo that brings up a good anecdote from my time in the archive, or at the collection?

Variety and dynamism can also be accomplished through the slides. Why am I the only one talking? Do I have audio or video clips that I can use? Can I call onto someone in the audience to answer a question? I often find it difficult to not sound monotone when I’m presenting. Embedding audio or video or planning for moments of interaction with the audience could help to break up the sound of my voice. There are also ways to make slides more dynamic and visually interesting without making them look unprofessional. If I need to talk over an image for a long time, how can I animate it in some way? Can I zoom in onto details of the painting as they come up in the talk? Can I show Calder’s mobile sculpture move? Can I play a video of the performance with the sound off as I’m talking about it?

The workshop I’m planning in Spring is an attempt to think about emotional engagement and diversity in the slideshow presentation as a group, without being prescriptive on which methods to adopt and when. I am aware that our cohort works in a variety of fields and from multiple identitarian positions that affect how we are perceived in a professional setting. Some of us can take more liberties when it comes to academic speaking and some of us cannot. But I am interested in finding out what people think about this comparison. Which methods of the video essay can apply to the academic presentation with the slideshow? I plan to use clips from videoessays to show some of these techniques. I’ll then play a clip of an academic presentation, and ask the people in the room to draw a storyboard of it. Storyboards, where a drawing of a shot and notes are put side to side, are very similar to the slide and script style of preparing for a talk. However, they force one in the position of the audience member instead of the presenter. They allow us to think in more detail about framing, and movement, and how to direct the attention of the viewer. I hope this exercise will inspire the group to think about some ways in which the slideshow can improve our ability to communicate our research to a variety of audiences.

Preparing for Leave

2026年1月14日 13:00

My wife and I are expecting our second child in just a few weeks, which means that I am gearing up for a new and chaotic phase of life. As a part of the preparation, I’m doing everything I can to keep things running smoothly for student programs in the Scholars’ Lab while I’m out. I set up a process for doing so when I took leave two years ago for our first child, so I’m not exactly working from scratch. Here’s how I’m preparing for my leave this time around to make things easier for my coworkers who will be keeping things going in my absence.

Give notice early

Everyone has different interlocking reasons for when they give notice to their team. Those reasons might be medical, personal, or professional. Given my own particular circumstances, I let my immediate collaborators in the Scholars’ Lab know fairly early, several months before I would be out. With this knowledge well in advance of the due date, my collaborators knew that I was taking steps to accommodate my absence. I also notified students who would be impacted. The dates I chose to take these steps were selected carefully in conversation with my supervisor, who helped me decide who needed to know and when.

Identify areas of responsibility

One of the first tasks in preparing to unplug for two months was to list my tasks, differentiating between major ongoing initiatives and smaller one-off items. This process helped me to create a to-do list such that I can make progress on my leave in a controlled manner. Otherwise, one can get lost in an anxiety spiral feeling like there is already more to do. I identified the Praxis Program, the DH Fellowship Committee, and our summer programs as primary initiatives in need of continuity.

Wrap up what I can

For smaller projects, I sprinted over the past two months to finalize whatever I could. Rather than working with a particular student on a weekly basis, for example, I set a date for a multi-hour meeting where we could make significant progress on their project. I set early writing goals for myself to meet deadlines in advance. And I took advantage of the slow down between semesters as space in which I could get ahead.

Establish points of contact for what I can’t

Some projects and initiatives will inevitably roll over through my leave. Working through my list, I worked with my supervisor and coworkers to identify people whom might be willing to take on specific pieces of my work. This process always involved asking my collaborators a series of questions: what do they need to feel comfortable? What can they do? What do they feel uncomfortable with? Who else might make sense for particular tasks?

Document everything

So much of the work I do exists in my head. Workflows, points of contact, procedures, norms. I tried to write as much of this down as possible so that someone stepping in would know exactly what to do and when. Winnie E. Pérez Martínez has been exceptional at working on this with me as a student worker, especially in regard to clarity and formatting. Winnie has a special talent for taking an enormous brain dump from me and assembling it into a coherent, less intimidating guide. I have learned a lot from her!

Put guardrails on future commitments

If possible, I tried to stop planning major commitments that would take place a couple weeks before the due date. At the very least, when I agreed to something, I made it clear that I might unexpectedly withdraw with little notice. I am also giving a couple weeks buffer before scheduling new commitments after I return in April. After all, babies have their own schedules in mind, and postpartum life is enormously challenging and complex. It’s impossible to know what our lives will be like for the next several months, and I tried to be honest about these facts with everyone involved.

Caveats

Everyone deserves the time and energy that parental leave allows to refocus on their personal life and meet the needs of a difficult transition. Everyone deserves coworkers kind enough to help them make space for their family. But I also know this is not the norm. I am enormously fortunate and privileged to have such support. That being said, I hope that what I’ve outlined above can be helpful even for those who do not possess such a robust support system. In those cases, this post might offer a rough guide for how to advocate, push back, and find small space for what you need in infrastructure that might not otherwise allow it.

3D Printed Cityscape

2026年1月8日 13:00

A screenshot of a map

This is a guest post by Makerspace user, Yifan Liu. During the 2025 Fall semester he developed and created a number of amazing cityscapes.

3D Print Tutorial: Cityscapes

By: Yifan Liu (yl3gm), UVA Graduate Medical Student

Creating a 3d Model

  1. Open the online software Map2Model. You will be presented with the following interface. A screenshot of a map
  2. Enter which city or area you would like to model search bar. Then select an area of the map to be modeled.
    A screenshot of a map
  3. Adjusting settings: There are many customizable settings that can be adjusted in the right-hand menus. Below are a few example settings that I commonly choose.
    • Base:
      • Map size: 152mm
      • Base layer: 4mm
      • Topography: Disable if modeling a relatively flat area to reduce complexity
      • Frame: Off
    • Features:
      • Roads
    • Include footpaths: Enable if you want to include detail of hiking trails or parks for example. Disable if you want to reduce file size and processing time
    • Road Types: Play around with disabling different road types for effect or reducing complexity - Grass: Off - Buildings:
    • Buildings Scale: 1.2x – 1.5x - Sand: Off - Piers: Off
  4. Press “Generate Mesh” to generate a 3d model of your selection A screenshot of a map
  5. Click the dropdown menu next to “Export 3MF”. Click “Export STL”
    • Note: you can also export as 3MF to retain features like roads, water, and buildings as separate objects.

Editing and Refining (optional)

You may notice that some structures in the model are not correctly detailed or rendered. If you want to add more detail, import your model into a 3d modelling software. For this example, I used Blender. More detailed instructions on how to use Blender can be found online.

  1. Download or create 3d models of desired buildings. Adjust to correct scale and position and place over existing building on model.
    A screenshot of a map
  2. Delete undesired geometry or vertices on cityscape.
  3. Export file as an STL for slicing and printing.

Slicing

  1. Open STL file in PrusaSlicer
  2. Adjust settings by going to “Print Settings”:
    • Print settings: 0.20mm Structural
    • Brim: 4mm
    • Infill: 10%
  3. Multimaterial Printing: (optional)
    • Click on the STL object and click on Multimaterial printing on the left-hand menu icons
    • Use the Smart fill tool to paint the desired colors. I prefer to paint water features blue and all other features white.

A screenshot of a map

Printing

  1. After slicing export your file to the desired printer. If using Multimaterial printing, use either Kermit (Prusa MK4 MMU3) or Big Bird (Prusa XL).
  2. Load and select desired filaments on printer. Make sure to check that the correct filament is paired with the correct extruder.
  3. Print and wait!

A screenshot of a map

Seeing, Describing, and Imagining: Human and Machine Vision in the Humanities

2026年1月3日 13:00

Framing the Workshop: Vision, Interpretation, and Context

In recent years, digital tools have quietly transformed how we experience and interpret images in museums, classrooms, and research settings. As an art historian working at the intersection of art history, digital media, and visual culture, I am drawn to examining how people translate visual experience into words, and how that process compares with machine analysis of the same images. I am especially interested in creating spaces that invite us to pause, pay closer attention, and make the act of interpretation visible, rather than treating images or technologies as self-evident.

Seeing, Describing, and Imagining originated from a simple, low-stakes classroom exercise I first encountered while serving as a teaching assistant in a course on formal and visual analysis taught by my advisor. Watching students work through the challenge of turning what they were seeing into words made it clear how tentative and negotiable description can be. That experience stayed with me and prompted me to rethink the exercise beyond the classroom, adapting it into a workshop format.

The workshop aims to create a shared, practice-based method for visual analysis that can be applied in various settings, from visual analysis courses to digital humanities labs, while staying rooted in art-historical approaches to looking.

From Looking to Language: Description and Interpretation

The workshop is conceived as a hands-on, collaborative way of exploring how images move between seeing, describing, and imagining. It is designed to begin with a simple exercise. Participants would look closely at an artwork and translate what they see into words. Working in pairs, one person would study the artwork and describe it in detail, while the other would create a quick line sketch using only that description, without ever seeing the image itself.

This phase aims to slow the process in a constructive way. Participants are encouraged to reflect on the act of describing itself: What do you choose to mention first, and why? Which parts of the artwork are hardest to put into words? These questions are designed to show that description is never neutral. Emphasis, order, and omission all influence how an image is understood.

When sketches and original artworks are placed side by side, the workshop is designed to shift from creating to comparing. Instead of viewing differences as mistakes, participants are encouraged to explore what moments of similarity and difference may reveal about the connection between image and text. The aim is not to fix these gaps but to use them as a way to think about how seeing, knowing, and describing are linked in art history practice.

Human–Machine Translation: AI, Images, and Visual Convention

Starting from this analog foundation, the workshop is structured to move into a digital phase by introducing AI text-to-image systems. Participants would revisit and refine their descriptions before entering them into an AI model such as DALL·E or Adobe Firefly. The resulting AI-generated image would then be placed alongside the original artwork and the participant-created sketch as a third object for comparison.

Rather than evaluating which image is better or more accurate, this stage emphasizes observation. Participants are encouraged to ask what kinds of visual patterns might emerge across AI-generated images. Which elements seem emphasized, simplified, or made more uniform across different outputs? Looking across multiple results is meant to create space for noticing patterns without assuming in advance what those patterns will be.

Existing scholarship by authors such as Kate Crawford, Safiya Umoja Noble, Ruha Benjamin, and Johanna Drucker suggests that AI systems are shaped by the datasets they are trained on, the ways information is classified, and the cultural assumptions embedded in those systems. Drawing on these works, the workshop is designed to create conditions where such influences could become visible through hands-on engagement rather than explanation. As participants compare images, the process opens up the possibility of exploring whether familiar visual conventions emerge, particularly when prompts involve artworks or visual traditions that are not widely represented in large image datasets. What becomes noticeable is deliberately left open and expected to take shape through comparison rather than as a predetermined outcome.

The workshop also introduces a reverse process, moving from image to text. Participants would upload an artwork into an AI vision tool and examine how the system translates the image into language. Reading these AI-generated descriptions alongside participants’ own interpretive accounts is intended to prompt reflection on differences in tone, emphasis, and confidence, and to raise questions about how uncertainty functions in human versus machine descriptions.

Staying with the Process: Open-Ended Inquiry and Reflection

Taken together, Seeing, Describing, and Imagining is framed as an open-ended inquiry rather than a demonstration. Prompt writing and refinement are approached not as purely technical tasks but as interpretive acts, similar to the analytical frameworks art historians use when working with images. While elements of the workshop align with existing practices in art history education, digital humanities, and critical AI studies, Seeing, Describing, and Imagining brings these approaches together in a distinctive sequence that foregrounds interpretation as an active, negotiated process involving both human and machine systems of vision.

The workshop is designed to foster attentiveness, curiosity, and careful comparison. It encourages participants to stay with the process and to observe what may emerge as images move between eyes, words, algorithms, and back again. In this way, both human and machine vision are presented not as stable endpoints, but as ongoing, context-dependent practices shaped by history, culture, and interpretation.

Works Cited

  • Benjamin, Ruha. Race After Technology: Abolitionist Tools for the New Jim Code. Cambridge, UK: Polity Press, 2019.
  • Crawford, Kate. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven, CT: Yale University Press, 2021.
  • Drucker, Johanna. Graphesis: Visual Forms of Knowledge Production. Cambridge, MA: Harvard University Press, 2014.
  • Noble, Safiya Umoja. Algorithms of Oppression: How Search Engines Reinforce Racism. New York: New York University Press, 2018.

Brighter Social Media Skies: Bluesky For Library-Worker (and DH!) Online Community

2025年12月14日 13:00

Social media can help you build professional and social community, find jobs, learn from others, share your work, ask questions, and hear about new ideas and projects. After the implosion of multiple other social platforms, the Bluesky platform has become one of the best options to keep accessing those benefits. This video captures a live webinar from May I gave for the Metropolitan New York Library Council, aiming to help library and archives workers considering trying out Bluesky, or who’ve dipped a toe in but not felt comfortable using it yet.

All the resources mentioned in this talk are listed at tinyurl.com/intro-bluesky. Most useful is my Bluesky for Academics guide at tinyurl.com/DHBluesky, which remains regularly updated and contains both very-quick cheatsheet and incredibly detailed versions of how to get started understanding Bluesky use for DHers, GLAM folks, and other knowledge work folks. At the end of that guide is a sortable list of “starter packs”, feeds, and lists gathering folks to follow on Bluesky around topics like DH, critical tech, expansive making & crafting, queer studies, social justice work, and more.

GIS Mapping Taught Through the Theory of Accompaniment

2025年12月8日 13:00

Geographic Information System (GIS) mapping attaches a dataset to a specific space and place, substantiating a relationship between the two as not only directly related but as affected by or moved to that specific point on a map. However, when thinking about how to teach a workshop on mapping to a group, one problem came to mind: we are in a generation with a profound lack of relationship to and with maps and the locations of countries. Which, in general, is its own point of discussion; however, when considering migration and mapping, a recognition of this lack became a focus for me. The question formed: how do I first get people not only to see, but really understand this non-relationship?

As students, we shape our own archives, perceptions, and pedagogy through the scholars we read and encounter. The scholar whose work inspired this very workshop, and answered the questions I wrestled with, is Ana Patricia Rodriguez. I was guided through my approach by both her first monograph, Dividing the Isthmus: Central American Transnational Histories, Literature, and Cultures, and her article, “The Art of (Un)Accompaniment: Salvadoran Child Refugee Narratives in the Twenty-first Century.” (10 out of 10 recommend others read both)

First The Non-Relationship

Rodriquez begins her monograph’s introduction with an activity she runs in her classroom. I pull that activity and use it as my own introduction to not mapping, but maps. The assumption I make is clear- Latin American countries do not and will not register as located within the group’s imagination. The lack is made evident. Now, no spoilers, go read her book. This part of the workshop will use 3D-printed or woodcut materials, is theoretically brief, and allows me to transition from map to mapping by asking them questions. I don’t know what I will ask quite yet, but they will be fantastic questions.

Accompaniment as Pedagogy

Next point of inspiration. First, the question. How can I make a GIS mapping workshop interactive and include a dataset based on migrant experiences in Mexico? Rodriguez’s article introduced me to the work on accompaniment. In this article, her reading of Javier Zamora’s Unaccompanied (also a book everyone should read), theorizes “a poetics of un/accompaniment” where,

The poems create a path of accompaniment of critical empathy for readers to follow literally and literarily the migratory routes of child migrants … It is in this process of accompaniment that readers are positioned, if not prodded, to question the conditions that produce child migration and the legal violence of migration policies, which shape the outcomes of arrival, detention, exclusion, and deportation, especially for women and children.

The accompaniment that Rodriguez traces in Zamora’s works and literature builds on scholarship and research on accompaniment in movements and research, but ties it to migration. Poetry and narratives create a different space for “readers to follow” migrants on their route to the United States. This, along with the ways readers are “positioned, if not prodded, to question the conditions,” prompted me to consider how a hands-on GIS workshop almost inherently, and unintentionally, seeks to enact an accompaniment. This is not to claim that there is a perfect or unflawed relationship between mapping and accompaniment. The accompaniment will shift a bit in its movement to the digital and/or in the making of narratives into data points. However, through accompaniment, what became clear was that what I considered to be simply an inherent relationship between place and data was flawed when I maintained it as inherent rather than as something to be questioned and interrogated.

The reality is that datasets can risk reducing humans to bodies in the very act of transforming information into points plotted on a map. That risk is exacerbated when the lack of relationship to a map is already present, and all a viewer intakes is a map filled with marks, even when they attempt to filter and narrow the scope of what they are looking at. With that, can embedding the mapping of points as a process of accompaniment shift how a viewer or a mapper processes a large, complex dataset? And is this shift my pedagogical framework? No clue, I will get back to you on that one.

The Actual Workshop

The nitty-gritty part of this actual blog post. Bear with me. In groups, people will be given a 3D-printed or woodcut of México, with holes already embedded into the country. These will be the data points (holes, literally just holes already made in the map) and pins, sized to fit them. The holes are rendered as a permanent facet of the map due to the nature of 3D printing, which makes me consider how the stories and narratives the map represents are always present, whether they are pinned and mapped or not. Which, by no means, should be uncomplicated, we should always consider why data gets mapped, what it is meant to demonstrate, what ends up entering, and what is left out and excluded.

Along with the country, they will also be given a mix of 14 notecards; on the front, each will have a year, the migrants’ nationality, and gender. In a longer workshop, I would leave parts of the data set unlabeled and have participants read the narrative on the other side and fill in the data themselves. Making data collection part of the activity and including a brief interrogation of what we synthesize and ultimately prioritize.

Mexico STL file

Closeup of Mexico STL

STL file for pins

Slowly but surely, they will place a pin on the 3D map at the final location in Mexico mentioned in the narrative, where the hole already exists. By this point, the idea is that each pin they place on the map will serve as an act of accompaniment.

After they finish plotting all the index cards, the hope is that the participant will also be struck by the magnitude and scatter of a map filled with data points everywhere. It is here that the final questions address an essential part of GIS mapping: how does one filter through large datasets? How important were those labels at the front of the card to begin with? How do all the parts work together? Does this data filtering return us to a different directionality of accompaniment? These questions, along with this workshop, are truly a work in progress. While the process of prototyping countries and pins has taught me so many things (like patience and a love of failure), there is still so much I cannot yet estimate. And any comments or suggestions are always welcomed with gratitude.

Finally, I have a big rule about recognizing the role people play in helping me make a chaotic idea from my imagination feel and become tangible. None of this would have been possible without the Makerspace, Ammon, Shane, Brandon, and, lastly, David Coyoca, the man I bother with all my questions about teaching, and who helped me sort through the chaos that is my brainstorming. This final version-in-process would not have been possible without the team effort that praxis encourages. 10 out of 10. Thank you.

References Rodriguez, Ana Patricia. 2009. Dividing the Isthmus: Central American Transnational Histories, Literature, and Cultures. Austin: University of Texas Press

———— 2025 “The Art of (Un)Accompaniment: Salvadoran Child Refugee Narratives in the Twenty-first Century,” Studies in 20th & 21st Century Literature: Vol. 49: Iss. 1, Article 8. https://doi.org/10.4148/2334-4415.2281

other possible lives in alumni data

2025年12月8日 13:00

It’s 2025 and too many of those enrolled in humanities PhD programs1 still think they’re going to land a tenure-track faculty position in higher education. Yes, Faculty2 members have been slowly facing the crisis of the academic job market, but even the most supportive ones are strapped for the resources, field knowledge, and the necessary time to effectively help PhDs navigate this landscape. Graduate curricula rarely includes comprehensive career training or coaching. This task falls almost entirely on academic advisors, many of which barely have time to keep up with their own work. How will they have time to educate their students about non-faculty careers? What happens if the tenured advisor isn’t even interested in engaging with the core issues of this challenging landscape? Who is going to support the PhD worker then?

Part of the academic job market problem is that we struggle to rethink the meaning of a successful PhD graduate in our times. We,3 scholars especially in the humanities, don’t know enough yet about non-academic networking to know or show what kinds of jobs, lifestyles, and interventions the humanities can create beyond the university. This is a challenge that haunts me, personally, as I’m soon-to-be in the job market for non-faculty academic jobs. It is also one that feels fundamental to answer for all of us who worry about the future of humanities scholarship and pedagogy.

One of my internship tasks this semester was updating the alumni data for two programs sponsored by the Scholars’ Lab: the Digital Humanities and Praxis fellowship programs, both yearlong DH-training opportunities for PhDs at UVA. Though there were preceding initiatives, the current structure of the Digital Humanities Fellowship is in place since 2007, and the Praxis Program since 2011. By now, there’s 121 combined alumni, many of which have graduated and taken on different positions. Some of those make great departing points for re-envisioning what success looks like for PhDs.

For example, humanities PhDs, did you know you have been gaining project management competencies all this time? I’d never heard about this field before I joined DH, but it turns out all that invisible work you put into completing your program gives you transferable skills that are highly valuable in project managers. Critical thinking, independent research, writing, pedagogical training, communication, and problem-solving are some of the core abilities we develop over time as we comply with the graduate and hidden curricula.

There’s also people who work as digital librarians/specialists within academic libraries. They engage, on different levels, with the training and education of known and emerging technologies, particularly those on the web. Think curriculum development, workshops, mentorship, library guides, project consulting, archival research, research assets creation and management. Are these abilities not akin to the training we acquire throughout the PhD?

Curators, consultants, artists, freelancers, programmers, developers, faculty, teachers, life coaches, housemakers, writers, editors, program directors. Those are some of the other careers and pathways of Scholars’ Lab alumni. Faculty and teaching-heavy jobs are only one genre of options. Why do we romanticize those positions and disproportionately teach PhDs to prioritize them? There’s so many things a humanities PhD can be. Why do we insist on feeding the neoliberal academy with our own bodies?

  1. I refer to them as PhD workers, not students, to better reflect their labor conditions. This change intends to recognize how the “student” misnomer erases the labor-intensive nature of any PhD experience, especially in the humanities, where funding is scarcer and the expectations for research, teaching, and service tend to be higher than in STEM. 

  2. "Faculty," as opposed to lowercase "faculty." The idea being that “Faculty” members are, in the end, always pro-institution and pro-status quo, regardless of any well-meaning intentions driving them. Then there’s faculty: those of the tenured kind who yield their power to say the uncomfortable truths, who do the extra admin work to make things happen for students in their program and colleagues, and who share their experiences to help others navigate the academic system. A dear friend shared this idea with me over the summer, and I can’t think of a better way to describe this dynamic. 

  3. I include myself, as a 6th-year PhD candidate in Spanish, Scholars’ Lab alumna and intern, and archipelagos managing editor. An insular Puerto Rican female that has now spent more than 10 years in higher education as a first-gen student and worker. 

Multilingual digital book arts (& an example accepted conference proposal!)

2025年12月3日 13:00

I’ve a talk accepted to the 2026 Global DH conference, and share that proposal here both for its content and as another example of what a conference abstract can look like. I’ve added comments (in ‘'’code formatting’’’) highlighting how the abstract proposal is structured.

“Not having to ask: critical humanities making, zines, & analog tech for multilingual DH”

In “Having to Ask”, a doctoral colleague [2024-2025 Praxis Fellow Amna Irfan Tarar] writes about othering experiences in DH spaces, such as when staff weren’t sure if a web font used by a team project could correctly render her name in Urdu. I’m developing digital and analog letterpress resources as part of our DH center’s critical humanities makerspace studies. Letterpress moveable type is a pre-digital corollary to multilingual web fonts, and Tarar’s essay reinforced my priority of anyone printing with us being able to print their name—without singling out that name as needing special effort or research.

Motivation / underlying research question.

This lightning talk covers the DH work I’ve started toward this goal, and will be of interest to scholars curious about: zine creation for teaching, critical humanities making, multilingual DH, accessibility, book arts, and connections between historical/retro tech and current DH methods. I’ll share my first set of moveable non-English type, my forthcoming zine on how to inexpensively create similar type, and an overview of my research into historical and current strategies for fabricating non-Latin type (some of which cannot be segmented into easily interoperable rectangles the way Latin type can). I know there are too many languages for us to complete this goal; while slowly moving toward that vision language by language, I’m also developing some quick hacks to at least slightly improve type accessibility in the mean time, as well as working to replicate how such scripts were historically printed.

Specifics on what the talk will cover. Which scholars might want to attend it and why, including showing how that's not limited to e.g. "people who do letterpress" or "makerspace people". Quick note that I understand the most immediate likely challenges to this work.

I’ve wanted to contribute to a more multilingual DH, despite my monolingual ability restricting what I can do. My hope is to develop enough type design and fabrication competency to partner with colleagues who have greater language competency than me, and I’m eager to hear advice from session attendees toward this goal.

Where is this in-progress research headed, and how might that benefit others? What kind of Q&A might this talk elicit from its audience?

Committee Questions

2025年11月20日 13:00

It’s application season in the Scholars’ Lab, which means that the DH Fellows program has a CFP live and waiting for new students to send in their work in. We’re also evaluating applications for our Praxis Program Fellowship, and we always have one student representative on the committee to read these applications. Students are closer to the program than we are, even as instructors, so they can help the staff see who will excel in the program. The students thankfully find it useful to be a part of the application committee. Students consistently say they learn a lot from seeing how application committees work, as it’s not a perspective that they often are able to get in their day-to-day graduate training.

I’ve written in the past a post called “questions to ask when applying” about what I wish applicants would ask themselves such that they produce the best applications possible. Questions like…

  • Do I know what the fellowship is?
  • Have I made a clear plan that matches the requirements?

Our student representative told me they have also found it illuminating to hear those questions that experienced application readers ask ourselves, as a committee. So, without too much elaboration, here are some questions that I always ask myself when reading an application for the first time.

  • How does this match the rubric? What’s left out?
  • How might the rubric be insufficient?
  • Who is a bad applicant that put together a good application?
  • Who is a good applicant who wrote a bad application?
  • To what degree are we willing to stretch our imaginations beyond what’s in front of us?
  • How much should we limit ourselves to the materials we have on the page?
  • Who might not yet know who they are?
  • Can we see something in an applicant that they don’t yet see in themselves?
  • Who will get something out of this opportunity they can’t possibly get elsewhere?
  • Who already has the resources to excel?
  • How can we build on the experiences of those who already have a lot of experience?
  • How can we balance the needs of the program with the needs of the applicants?

I’ll leave these hanging as questions, because the answers are things that any particular committee will have to find for itself. But hopefully enumerating them here give future applicants a resource that they can look to while also giving students a peek behind the curtain. The next time you’re putting together an application, think about what questions the evaluating committee might be asking themselves.

The Gift We Give

2025年11月7日 13:00

As I’ve written in this space before, I’m working on a book project and recently hit a major milestone. I finished developmental editing and initial proofing just last week, and I compiled the whole thing together into a complete manuscript for the first time. I printed the text out for one last proof front to back before I send it out. This means I suddenly have a physical copy of the whole thing for the first time. It’s forty pages longer than my dissertation. Exciting! Feels real and substantial. So much so, in fact, that during my 1:1 meeting with Amanda Visconti I slapped the bundle on the table in front of us.

“Check this out!”

Amanda is an incredible mentor, collaborator, and friend. They’ve been hugely supportive of my work, but especially so about my writing process. I knew they would be excited to see the result. What I couldn’t expect was that Amanda would take my print manuscript, hold it to their chest, and say, “Thank you so much. Getting this has made my day so much better.” I hadn’t intended the printed draft as a gift, but I couldn’t really take it back after a reaction like that. I went back to my laptop and printed out a second copy for myself to replace the unexpected gift.

We should all be so lucky as to have friends and mentors who react to our work like this. The moment was especially meaningful to me as somebody who has all the associated anxieties and imposter syndrome about their project not being good enough. It is so easy to see something only for its flaws and not to see the impact it might have on others even with all its messiness. I wasn’t ready to share my manuscript with Amanda, but I did so anyway.

With the world such as it is, I’ve been thinking a lot about what it’s all for. Why do we write? Why do I write? Who is reading? Does any of it really matter? We all hope that our writing can have some sort of impact in the world, but it’s so rare to see its effect in a tangible way. The same day, Dr. Emily Friedman posted to Bluesky about social media as a space where one can find comfort in “the stars of hope on the far horizon, as here night seems without end.” Friedman’s post resonated so much, in no small part because I find them to be such an inspiring scholar. So often we quietly take hope and inspiration from people that we never meet and they never hear about the effect they’ve had on us.

So I share this small moment for others who might be struggling with their own motivation or with their own perception of their work. Whether you see these kinds of reactions or not, your work matters. You matter. Keep writing. You never know who might clutch your manuscript to their chest when they find it. You might be sharing an unexpected gift someone needs.

For those us of finding hope in the work of others, may we all be more vocal about it.

what dh labor talk did for me

2025年11月4日 13:00

Graduate students workers are a lower class form of contingent labor in higher education, although a privileged one. Grad workers supply essential labor to universities for a fraction of a faculty/lecturer salary. As a direct consequence of their contingent status, graduate professional development is rarely a priority in the daily operations of a doctoral academic curriculum. Institutional needs always come first.

Many grad workers come into PhD programs unaware of this dynamic and how it decisively shapes our professional outlook during and after the program. Others, like me, have been exposed to its reality through sour personal experiences and conversations with mentors, colleagues. Even so, I know we remain at least partially in the dark about the ramifications that being cheap, contingent workers have on our role and responsibilities as workers. We graduate without fully realizing the extent to which being employees in a knowledge company affects our ability to afford basic necessities, like rent and food. Partly, this happens because cloaking the commodification of higher education has become part and parcel of academic culture.

For me, it was in the digital humanities community (DH) where I started feeling more like a colleague than a student. In this space, I met people who helped me see, understand, and navigate my position as a higher ed worker. Why is it that some realities of labor are more visible in DH spaces? Why is it so hard to talk about labor in academic ones?

Academic scholarship, for historical and cultural reasons, holds the allure of being a virtuous pursuit, the always-noble goal of producing and managing human knowledge. Scholars are the watchful guardians of humanity’s archive—or that’s supposed to be the idea. Many apply to grad programs hoping to join a knowledge-driven guild. In reality, joining this grand purpose also means inheriting a set of intellectual hierarchies, values, and practices that have as much to do with oppression as they do with knowledge-production and pedagogy. It is easy to forget that, after all, the university is a centuries-old product of early Christian European ideas of knowledge-making and learning. This means that the dedication of the “Academic Ivory Tower” to the pursuit of knowledge also includes strict models, formats, and biases about what scholarship means and looks like, who can produce it, what makes it valid, and how it turns into knowledge.

This long tradition of academia as a space for intellectual exchange is what still draws many of us to its campuses, what compels us to dedicate long hours to reading, writing, thinking. We collectively subscribe tacitly to the belief that the university is a safe site for intellectual exchange and learning. Such an idea hides institutional interests and dealings in politics and funding to, instead, present the university as an intellectual safe-haven. The hidden underbelly reveals a for-profit institution looking to capitalize its assets (human and otherwise) to their maximum potential, often as cheap as possible.

In this system, the love and devotion for sharing knowledge that is inherent to the role of lecturers, faculty, and graduate PhD workers becomes entangled with the amount of labor they individually generate for the university.1 But these conditions aren’t immediately visible in everyday life. It takes time, exposure, good guidance, and effort to see the small ways in which they end up significantly shaping career outlooks, especially for grad workers. You’re caught between being a student (someone who takes courses), a teaching instructor, a research assistant, and a researcher-in-training. You’re meant to defer to your advisor and/or department when you take on new commitments, projects, applications, and they sort out the administrative side sometimes without much explanation. Institutional rules and regulations are not to be your immediate concern, much less your focus. You’re theoretically expected to fully focus on your research. But these rules hold the bureaucratic and capitalist nuances that govern the existence of your position as a grad “student” worker.

DH offered me, instead, a space to meet, listen, and learn from a community of scholars that do not all hold traditional tenure-track placements. Many are librarians, research specialists, programmers, admin directors, or officers. Regardless of job title, these are the kind of worker hired generally under the label of “staff.” Their salaried conditions play a daily role in their workplace interactions and their position’s descriptions are more granularly described than “graduate student” or “dissertation committee member,” for example. This varied constituency, in turn, supports the development of DH’s overt disciplinary concern with the job crisis in higher education at a time when traditional graduate school curricula aren’t evolving quickly enough to protect graduate workers from the crisis. Professionalization in DH goes hand in hand with discussions about pedagogy to address job uncertainty, job market survival skills, alt-ac opportunities/training, and hidden curriculum issues.

A landscape where labor is frequently discussed creates the space to consider the necessary individual, personal, material needs that we each require to become fulfilled employees amidst current broader issues of social and economic decay. A space that acknowledges multiple forms of expertise, abilities, and needs, also highlights that one single person—no matter their desire and experience—is incapable of single-handedly supporting a grad worker’s growth as a professional. DH pushes grad workers to seek and foster a community of colleagues to navigate the brutal job market where the traditional graduate curriculum dictates graduate student workers should always do what their advisor says.

  1. Katina Rogers explains this directly proportional relationship in the essay “Covid, Care, and Community: Redesigning Graduate Education in a Pandemic,” published as part of the Digital Futures of Graduate Study (U of Minnesota Press, pp.3–12, 2024). 

Filling the Cup of Each Writing Phase

2025年10月28日 12:00

Given that I work with graduate students at different stages of their PhD journey, it’s probably no surprise that I have many versions of the same conversations.

How do I write my dissertation?

How did you write yours?

In my experience, students struggle to maintain a sense of progress while writing their dissertations. Those perfectionist tendencies that got them so far in life can cause real problems when working on a two-hundred-page document. I had a very careful process for my dissertation writing and for managing those frustrations. Process can be one of the things that saves us from the tyranny and the blank page, so I thought I would share two things that students seem to find inspiring: how I wrote my dissertation and how I go about writing now.

My dissertation process

I often say that I wrote my dissertation at five in the morning. There is some truth to this: I used to be teaching assistant for a study abroad program in London each summer. When I came back to the States, I always found myself jet-lagged and awake at five in the morning. Each summer I kept the jet lag going as long as possible and wrote before anyone else was awake. This sleep habit eventually evolved into a broader strategy: write in the morning and research in the afternoon. Each dawn I wrote until I hit a fairly modest writing goal. After lunch, I spent whatever time I had remaining researching the material that I would then incorporate into my writing the next morning. This schedule was obviously impossible to maintain during seasons of the year when I had meetings and other obligations. But one consistent through line was that I always had a clear goal whenever I sat down at my laptop.

In the afternoon, I didn’t feel the pressure to write because I had already made progress in the morning. And I knew in the afternoon that I my only goal was to set myself up for success the next day, to provide material for when I next sat down to write. I started each morning confident that I knew where to begin. Writing in this formulation felt like riding a train and constantly refueling it to keep it moving. This past week our Praxis student Jimga introduced me to the saying “you can’t give what you don’t have,” an idea that describes the core of my dissertation writing process. The most important part of my process was ensuring that I had more to give.

My process now

I don’t have the luxury of much unstructured writing time with my current full-time gig, but I have clung to and refined certain pieces of that process-oriented approach. In Molly McCowan’s Great Course on Effective Editing, she divides editing into several different phases: developmental editing, line editing, copy editing, and proofreading. The discussion helped me to see my own writing as stepping through a finite set of moments: brainstorming, drafting, developmental editing, proofing, and finalizing. One of the most powerful things you can do for your writing is to recognize that each phase is distinct. Even writers who are fairly advanced might sit down to the page without a clear goal in mind, without knowing which phase they are in. It’s even more challenging to keep your brain from wanting to slide between phases. You might well think you’re sitting down to proof, but before you know it you find something that you need to change. So you make one small edit. Then another. And another. Before you know it, you’re back in the drafting stage. You feel stuck and like you haven’t made tangible progress.

Whenever I find one comma out of place while proofing I suddenly feel as if the whole page is destabilized. I feel like I have to reread the whole thing again. I need a way around this sense that things are always changing, and my way to do so is twofold. First, always sit down with a clear goal when getting ready to write. Second, differentiate the phases of the writing process by actually making them feel different. I mean this quite literally: I have gotten in the habit of using a different tool for each of the stages of the writing process. Most of my drafting I carry out by dictating into my phone while driving to work. When I sit down for the next stage—developmental editing—I have some material ready to go that I work on in a fairly typical word processing environment. When I am ready to proof, I actually print the document out and do so by hand. I find that if I work with a pen I just cannot make the kinds of edits that might come if typing on a keyboard. Instead, I wind up with a very targeted set of changes for my last step, when I go back to my laptop and integrate the handwritten changes into a final document. I have a to-do list, something finite. I know exactly what needs to change, because I have those ink marks on the piece of paper rather than an infinite sea of possibilities.

Each prior phase fills the cup for the next one. I end each session with what I need for tomorrow, a gift for the writing to come. When I sit down for a new phase I find that I now approach it with purpose and gratitude for my past self. Does the system look like chaos to the outsider? Maybe. But I also think of writing as an encounter with chaos every single time you sit down with a new document and expect to find some order in it. My system helps ensure that the page never stays blank for long.

Defining Digital Humanities By What It Is Not

2025年10月27日 12:00

The following guest post comes from Filadelfia Soto. Soto is a second-year doctoral student in the Spanish, Italian, and Portuguese Department at the University of Virginia, where she is also pursuing a Digital Humanities certificate. She is interested in how technology can support the study of colonial archives and amplify voices historically underrepresented in traditional scholarship.


The hardest part about explaining Digital Humanities is that it refuses to fit into a single definition. Sometimes, to understand a concept, we must begin by clearing away what it is not, and Digital Humanities is a perfect example.

Try explaining Digital Humanities at a family dinner, and you will quickly realize how slippery the term can be. This October, I attended the 7th Digital Humanities Conference in Monterrey, Mexico. An international event at a well-known Mexican university that gathered humanists from around the world who integrate technology into their work. Therefore, one could say that we were a group of digital humanists. However, when at the final closing session, after three days of learning and enriching collaboration, the moderator asked “Colleagues, what is Digital Humanities?” We all sat in silence. After the awkward silence, the moderator continued, “then, what is Digital Humanities not?” I was deeply hooked. Sometimes, when attempting to explain what something is feels difficult, it becomes easier to begin with what it is not.

Digital Humanities is not one discipline but a multidisciplinary approach that combines computing and the humanities to strengthen research methods and outcomes. It is not about replacing the researcher with a digital tool. Rather, the focus lies on identifying or designing tools that complement and enhance human inquiry.

This led to questions that resonate deeply to me as I am a novice digital learner: How much computing should a humanist know to engage in a Digital Humanities project? Do we need to learn programming? The researcher does need to develop computational skills, but the kinds of skills required depend on the nature of the project. As a multidisciplinary field, teamwork is essential; it optimizes time and effort, strengthens results, and fosters a community of shared expertise. Digital Humanities is not a one-person endeavor.

Lastly, Digital Humanities is not the indiscriminate use of computers for any and every task. While humanities projects often begin with a problem, Digital Humanities projects arise from a specific need. For example, a historian might start with a question about migration patterns; the work becomes a Digital Humanities project when digital mapping is required to visualize and better analyze those patterns. In essence, the humanities address the problem until technology becomes necessary to enhance performance and results, then the digital component steps in!

The ideas presented here reflect my current understanding of the Digital Humanities field. This is a field that, as I realized during the closing session in Mexico, continues to resist a fixed definition. My intention is not to assert a definitive position but to keep exploring what Digital Humanities is and is not. Through this writing, I hope to invite dialogue and collective learning among those equally curious about the subject.

Mapping Queer Belonging

作者leo-palma
2025年10月21日 12:00

I want to take this first blog post as a chance to write down some reflections prompted by these first months of the Praxis program. Most notably the conversation with Jeremy about the big “why” of Digital Humanities projects in relation to Frank Chimero’s Shape of Design, Zarif’s and Jess’ presentations on poetry and novels, and Drew’s presentation on GIS.

I have been thinking of creating a digital map of Fiore de Henriquez’s (1921- 2004) artworks in their current location. Fiore was an intersex artist and sculptor from Trieste, my hometown, and I have been researching her works as part of my dissertation. While she received commissions from all over the world, the locations of her artworks are largely unknown and not publicised. I have been wondering whether my mapping of her practice should include the artist’s over-the-top stories about her experience of gender difference, as performative acts through which the artist expressed her view of herself and her work. These tales often contain elements of fiction, but they always take place in highly recognisable and memorable places. Thinking about my “why” for this project, and about what it might look like, I was reminded of Queering the Map.

Queering the Map was created by Lucas LaRochelle in 2017, in effort to re-think how queer geographies of space are usually conceived. It anonymously archives queer experience in relation to place via a pink map with black pins, to which anyone in the world can add their own contribution. This collaboration inevitably results in “something that is fundamentally messy, contradictory, and confusing” (LaRochelle, 2019). Some pins are jokes, some are cryptic, some read as reviews of certain locations, others are confessions, personal and heartfelt. Some are tragic and filled with grief.

Repeating a fairly common sentiment, LaRochelle expresses that his “why” was “to contribute to the life-sustaining force that is queer internet culture”, citing his own life-changing experience in digital queer spaces, which made up for the nonexistence of queer places in rural Ontario, where the author grew up. However, I see this map as doing something else. To me, it complicates the narrative of the digital as a place for queer connection when the local is a place of queer solitude and loneliness. Instead, the digital anonymous character of the map makes visible the multiple, contradicting, sometimes imagined ways a place can be queer. It expands the common reduction of queer spaces to bars, clubs and saunas. Instead, it makes visible the multiple, complicated ways any place, no matter how homophobic or transphobic, can be made queer.

Some comments on the map are clearly not interested in recounting real events at all – some pins in the middle of the ocean include comments like “made out with a mermaid :)”. Even for those that seem earnest, there is no guarantee that the pins have been placed in the actual street where the events narrated took place, nor if the events recounted even happened at all.

Reading random pins on this map, I am reminded of Fiore’s way of telling her life stories as half-made-up tales. They also remind me of a poem by Umberto Saba, (1883-1957). Umberto Saba is the only writer from my hometown, Trieste, that is included in high school textbooks around the country. As an Italian irredentist, he’s one of the few writers from the regions that fits the state’s nation-building narrative. I have studied his poems many times, learning them from memory as early as elementary school. But I was never told he was queer, nor that he thematised his experience of queerness in a number of his poems and novels. Here is one of his most famous poems, titled “Trieste”:

Ho attraversato tutta la città.
Poi ho salita un’erta,
popolosa in principio, in là deserta,
chiusa da un muricciolo:
un cantuccio in cui solo

siedo; e mi pare che dove esso termina
termini la città.
Trieste ha una scontrosa
grazia. Se piace,
è come un ragazzaccio aspro e vorace,

con gli occhi azzurri e mani troppo grandi
per regalare un fiore;
come un amore
con gelosia.
Da quest’erta ogni chiesa, ogni sua via

scopro, se mena all’ingombrata spiaggia,
o alla collina cui, sulla sassosa
cima, una casa, l’ultima, s’aggrappa.
Intorno
circola ad ogni cosa

un’aria strana, un’aria tormentosa,
l’aria natia.
La mia città che in ogni parte è viva,
ha il cantuccio a me fatto, alla mia vita
pensosa e schiva.
I traversed the entire town.
Then I climbed a steep slope,
crowded at first, deserted further up,
closed by a low wall:
a nook where I sit

alone; and it seems to me that where it ends
the town ends too.
Trieste has a surly
grace. If one likes it,
it is like a rascal, harsh and voracious,

with blue eyes and hands too big
to offer a flower;
like a love
with jealousy.
Up from this slope every church, any street

I discover, whether it takes to the huddled beach,
or to the hill where, onto the rocky
top, a house, the last one, clings.
All around
circles all things

a strange air, a tormented air,
the native air.
My town that is in every of its part alive,
has a nook made just for me and my life,
pensive and reserved.

Saba sitting by the bay overlooking Trieste, 1951

Saba sitting by the bay overlooking Trieste, 1951

In this poem the bird’s eye view on the territory allows the poet to see the city in all its contradictions, both crowded and deserted, teeming with life but with quiet, solitary corners. After the difficult ascent to earn such a perspective, the poet finds within these contradictions a sense of belonging. The strange, tormented air is recognised as denoting home. When I studied this poem in school, this sense of belonging was taught as a general one, but I always felt it was queer, even before knowing of Saba’s sexuality. Specifically, the personification of Trieste as a “ragazzaccio” struck me as significant.

Cities are usually personified as female in art and literature. They are to be defended, and protected, they are the “motherland” of the masculine citizen. At the same time, they are also lovers of the presumed male citizen, and the love for one’s hometown needs to be established as a heterosexual one. This is even more explicit in Italian, where they are grammatically gendered female, as in most romance languages. Here however, Trieste is a boy, and a bad boy at that. He’s sweet but rough, he wants to consume and take – he’s voracious – but is unable to be delicate and give anything back, not even a flower. The city is transitioned into an image of an imperfect boy, who the poet cannot help but love in an imperfect way, with jealousy. The poem is queer because it transitions the city in order to make the love between the poet and the city a queer one. I read it as a queer outlook onto the landscape, one that generates a queer sense of belonging and personal peace. Like in Queering the Map, the view from above reveals the multiple, complex, and contradictory ways the landscape is lived in. Among these is the “cantuccio a me fatto”, a small and hidden but safe place for queerness.

These have been some thoughts inspired by these first few months of class. While I have largely used the case of Trieste to work through some of them, I wonder how they might resonate beyond this case study (and I must thank Eleanor for her comments about how they spoke to her own experience). As I am figuring out what my DH project on Fiore will look like, I will keep thinking about Saba and Queering the Map, and whether the digital, with its ability to reunite at a glance such diversity of experience, can make visible how queerness inhabits unlikely places.

Works cited:

  • Chimero, Frank. The Shape of Design. Frank Chimero, 2012.

  • Co-Creation Studio at MIT Open Documentary. ‘Co-Creating a Map of Queer Experience’. Medium, 2 November 2019. Link

  • Queering The Map. ‘Queering The Map’. Accessed 12 October 2025. Link

Poem Translation:

Literaryjoint. ‘Trieste, by Umberto Saba, English Translation’. LiteraryJoint, 6 March 2013. Link

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