Bibliographic record
Abstract
As a rule, translation “nurtures” a text, extends its genealogy across cultural and historical divides. The strange account of this article is perhaps the exception that proves the rule. We’ll see a seventy-year old Jorge Luis Borges put heads together with a young Harvard man by the name of Norman Thomas di Giovanni and “re-write the slate clean,” translate old texts for the purpose of “sticking it” to them, suppressing them, even consigning them to oblivion. The collaboration was a bit of inspired naughtiness that we’ll call “translational infamy.” It had enduring consequences, for the good and bad, on the characters populating Borges’s writings and his private life. This equation of translation and oblivion, we’ll see it play out in Borges’s older fictions, specifically Pierre Menard; in the editorial logistics of his collaboration with Di Giovanni; in the creation—and simultaneous translation—of new fictions (Brodie’s Report); and, perhaps most interestingly, in the details of his own biography.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.048 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".