“We Are Text”: Reading, Dwelling and Narrative Identity in Michael Ondaatje’s The English Patient and Divisadero
Bibliographic record
Abstract
Outlining two ways of thinking about the relationship between speaking and writing—one which holds speech as anterior and superior to writing, which it sees as a secondary system of representation, and the other which views speech as being a form of writing itself operating within the play of difference and deferral that is language as such; the essay suggests that the two novels in question propose a third position that contains elements of both the previous two. This position is captured in key instances in both The English Patient and Divisadero of the written word being read out loud in a communal setting. In view of Lucien and Marie-Neige’s and Hana and the English patient’s practice of reading out loud to each other, Divisaderoand The English Patientsuggest that reading—whether it be studious, curious, or otherwise escapist in nature—is a vital act of incorporation, a political act of consumption wherein words become flesh and the stories in books come into confrontation with the texts of our selves in an explosion of intertextuality.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.030 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".