CONTRASTING STACK-BASED AND RECENCY-BASED BACK BUTTONS ON WEB BROWSERS
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
People frequently use the ubiquitous Back button found in most Web browsers to return to recently visited pages. Because all commercial browsers implement Back as a stack, previously visited branches of the tree are pruned; this means that people can quickly navigate back up the tree. The problem is that previously seen pages on alternate child branches are no longer reachable through Back. An alternate method is to implement Back on a recency model, where all visited pages are placed on a recency-ordered list with duplicates removed. This means that all previously seen pages are now available via Back. Because advantages and trade-offs exist in both methods, we performed a study that contrasted how people used stack vs recency-based Back. We found that people have a naïve mental model of how the conventional stack-based Back works, typically perceiving it as a recency list. People are also poor predictors of what pages will be displayed with both types of Back buttons. Finally, people seem evenly split over their preference of a stack vs recency-based Back button.
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