Interaction History Support for Web Applications
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
All users of complex software make decisions that they may later wish to change. Many computer systems have tools to support this need for revision, such as the undo command. However, the common history tools (like undo) do not support exploratory, epistemic interaction well. And there are common, non-specialized tasks that are difficult in common computer systems, but would be much easier with improved support for managing interaction history. Desktop computing environments have well-established norms for how undo works, but there is room to explore this in newer computing environments, such as the Web and surface computing, as their design culture has not stabilized to the same extent. We argue that history tracking needs to be more accessible to users.We developed a prototype JavaScript library for Web applications that lets users keep a history of all their interaction states, including those that would be discarded by using a traditional stack-model undo system. The history is presented to users in a tree structure similar to the model used in source control software. We ran a usability study of our system with two applications designed to encourage the kind of exploratory behaviour we wanted to support. We identified usability improvements that could be made, but the study suggests that this kind of system could be generally useful even in non-specialized fields.
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 | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it