Chapter 11</br>Designed for the digital reader: The textual traditions in, of, and behind NewRadial, the dynamic table of contexts and Bubblelines
Bibliographic record
Abstract
This chapter examines the various textual traditions that inform the design and affordances of three INKE digital tools, namely NewRadial, the Dynamic Table of Contexts, and Bubblelines. In turning to earlier textual exemplars, such as the sammelbände and foldout engravings, the chapter illustrates certain commonalities between past and present textual media. Similarly, by examining the material evidence of Renaissance readers, including manuscript tables of contents and supplements to print indexes, the chapter considers the long history of customization that lies behind many of our digital applications today. In short, the chapter invites readers to situate a series of INKE tools within a much earlier and seemingly unrelated textual tradition. Ce chapitre examine les diverses traditions textuelles qui guident la conception et les affordances de trois outils numériques INKE, c'est-à-dire New Radial, the Dynamic Table of Contexts et Bubblelines. En examinant des exemplaires de référence textuels plus anciens, comme le sammelbände et les gravures reliées, le chapitre illustre certains points en commun entre les médias textuels anciens et actuels. De la même façon, en examinant les preuves substantielles des lecteurs de la Renaissance, y compris des tables des matières manuscrites et des suppléments à des index imprimés, le chapitre étudie la longue histoire de la personnalisation qui se cache derrière bon nombre de nos applications numériques de nos jours. Bref, le chapitre invite les lecteurs à situer une série d'outils INKE au sein d'une tradition textuelle beaucoup plus ancienne et apparemment sans lien.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.055 | 0.017 |
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".