Bibliographic record
Abstract
Abstract: Inspired by the fictional construction of Stephenson (2000), an “anfractuous ” book able to answer reader’s questions by self-expansion and ramification, and functioning on the principle “tell me more about this subject”, our project deals with the construction of an interface allowing several levels of detail and implying different “scales ” of textual rep-resentation. By revisiting a number of traditional narrative paradigms, the paper will discuss some new possible ways of storytelling determined by this kind of textual development and exploration. Greenblatt (2004) suggests that in “Venus and Adonis”, Shakespeare uses a way of approaching or distancing the reader from a character or situation by increasing or decreasing his “physical and emotional proximity”. In some passages, we seem to be at a great distance from the two protagonists while in other, we can observe the tiniest details, as in a view evoking the “zoom in ” perspective. On the other hand, in his analysis of Evelyne Waugh’s “Vile Bodies”, Alan Palmer (2003) uses the term “behaviorist narrative ” defined
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.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
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".