User Interface Constraints to Influence User Behaviour when Reading and Writing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Constraints are fundamental to human-centered design. Although by definition, constraints “limit” or “restrict” the capability of software, when designed correctly, they can have enabling characteristics as well. In my dissertation, I seek to understand how user interface constraints can influence user behaviour when reading and writing text. First, I discuss a document reader with auto-scrolling to facilitate time-bounded reading for increased focus. Second, I contribute the idea of limiting how much text can be highlighted in a document to encourage readers to think more about what is truly important in the document. Lastly, I discuss how constraining an AI writing assistant through prompts with varying levels of detail may improve a writer’s feelings of ownership. Through these three projects, my dissertation will contribute novel constraints-based interaction techniques that can be integrated into new or existing systems, which is of interest to the UIST community and the HCI community more broadly.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it