A Mandala Browser User Study: Visualizing XML Versions of Shakespeare's Plays
Bibliographic record
Abstract
We report he results of a small user study of a visual XML browsing prototype, called the Mandala browser, where dots representing entire documents or portions of documents are plotted around the periphery of a circle and drawn inward by colored magnets that are assigned values by the user. The result is akin to a Venn diagram that provides a visual representation of the interaction between multiple Boolean queries. In this study, eleven participants were given a pre-study interview, then asked to carry out a series of tasks where the dots represented speeches in plays by Shakespeare and finally were debriefed in a concluding interview. We gained from this study a range of valuable insights into how details of the Mandala browser design could be improved. Participants mentioned, for instance, that they would like to retain a connection between results and the visualizations that produced them, that they would like to be able to make notes on result sets, and that they would like to be able to save subsets within results. They also asked for tools that support collaborative searching, as well as for federated searching across collections. The user feedback confirmed the potential value of the Mandala interface and provided guidance for the next iteration of development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".