Challenging new views on familiar plotlines: A discussion of the use of XML in the development of a scholarly tool for literary pedagogy
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
This article describes PlotVisML, a simple, flexible XML schema for encoding literary narratives that was developed by an interdisciplinary team of researchers in literary studies, interface design, computing studies, and education as part of a research project on reading, writing, and teaching complex literary narrative. PlotVisML is a simple, adaptable schema consisting of five key elements: <action>, <dialogue>, and <narration> (tags for marking up narrative events), and <character> and <object> (tags for encoding narrative objects). Fictional narratives that have been marked up using PlotVisML can be visualized in PlotVis, a digital scholarly tool that allows users to model and interact with literary narratives in three dimensions. Both PlotVis, an interactive visualization tool, and PlotVisML, our custom XML schema for encoding literary narratives, were designed to permit challenging new views on familiar plotlines and, more importantly, to depart from conventional ways of modeling narrative in literary instruction. In discussing the process of developing PlotVisML, we contribute to the ongoing discussion of text encoding as a form of close reading (e.g., Liepert, 2009).
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 | 0.000 | 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 it