Grabbing Life by the Ballot: Creating an Effective Ballot through Design
Bibliographic record
Abstract
This presentation, reflecting a politics undergraduate thesis, will explore the design process behind the ballots that voters use in democratic elections around the world. Ballots are an inherently political objects, and in many cases, the most direct line of communication a citizen has to the government of their country. As such, the design of the ballot affects the legitimacy of higher level electoral and democratic institutions. This project argues that by co-opting the language of product design, a universal ballot design process would make more efficient ballots across the globe.
 
 Product design starts with a brainstorming stage that explores at the user, the goal of the object, and the context of its use to create an effective design. By applying these observations to the process of designing a ballot, each electoral commission can produce a more effective ballot. Currently there is no standardization for ballot design other than ensuring that electoral commissions tried to make it “friendly.” By examining cases of bad ballot design, it is possible to see what element of the design process was missed or misused to create a process that corrects for these mistakes. This project examines poorly designed ballots in Florida, Scotland, and Colombia to explore the large-scale effects these small design choices make, and how to fix them.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".