"I wanna die just like JFK / I wanna die in the USA": Libra and DeLillo’s Curation of the Kennedy Archive
Bibliographic record
Abstract
Don DeLillo reimagines and revisions the Kennedy assassination in Libra. Nicholas Branch, a retired senior analyst for the CIA, has been hired on contract to write a definitive account of the events at Dealey Plaza on November 22nd, 1963. In the process, Branch subsumes the role of the museum curator; he meticulously combs through the received records in order to challenge accepted versions of “history”. As the novel’s character-as-curator, Branch examines, positions, interprets, and displays the artifacts at hand to outline the numerous plots swirling around the assassination. This paper will demonstrate how DeLillo, through Branch, reimagines the space of the novel, transforming it into a museum display that challenges the Warren Commission’s “Single-Bullet Theory” and its “Lone-Gunman Theory”, to instead suggest the possible presence of multiple shooters. As the novel’s character-as-curator, Branch meticulously places the objects on display and leaves it to the reader to decide which view to adopt or accept.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".