The Role of the Working Space Representation and Epistemic Interactions in Map-based Visualizations
Bibliographic record
Abstract
At present there are many asynchronous programming interface-enabled digital maps (e.g., Google Maps, Google Earth, MSN Virtual Earth) that can facilitate map-based visualization of documents (such as newspaper articles, metadata records, journal papers, books, medical records, job or real estate listings).These maps have built-in interactions which allow users flying through the space, panning and zooming to any location, rotating maps for proper orientations, traveling through time, and viewing linked items.Absent is such maps are tools for higher-level cognitive activities such as information foraging, exploration, sense making, and collection understanding.Geovisualization researchers (MacEachren, 1995;Pequet & Kraak, 2002; Edsall, 2001 and other) might argue that map representations alone can facilitate high-level reasoning activities.But cognitive researchers suggest that epistemic interactions and the representation of the working space may enhance user's performance in reasoning activities even more (Kirsch, 2009; Maglio, Matlock, Raphaely, Chernicky, Kirsch, 1999;Kirsh, 1995b).This paper presents a conceptualization for augmenting map-based visualizations of documents with epistemic interactions and the representation of the working space.
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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 | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".