Spatial Reading: Digital Literary Maps of the Icelandic Outlaw Sagas
Bibliographic record
Abstract
Digital humanities scholarship contributes to current conversations on literature in many forms, especially in its recontextualizing of what it means to read. By integrating visual, spatial, and quantitative forms of knowledge alongside the practice of text-based hermeneutics, digital techniques expand the possibilities of interpreting texts, particularly with the emergence of widely available geospatial and data visualization tools. This article outlines and reflects on a methodology for producing geospatial and data visualizations of place names in the Icelandic outlaw sagas, and discusses how the results corroborate existing research and also facilitate critical methods of ‘reading’ these texts spatially. While articulating the saga-specific findings of the visualizations, this article also contextualizes the conceptual work of digital literary mapping as a method that is particularly insightful as we determine the role and validity of digital techniques, especially for interdisciplinary and historically-situated work.
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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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".