Bibliographic record
Abstract
Abstract: According to Marthe Robert, the novel Don Quixote raises the question of the truth of literature: “What place do books have in reality? Are they absolutely true or true only relatively?… If they are false, their very fascination makes them useless or harmful and they must be rendered null and void, or better still, burned.” This article explores the pertinence of this question to the writings of Kierkegaard, who was preoccupied by images of fire and burning as well as by questions of the ultimate adequacy of literature, including his own “prolix literature,” to communicate Christian truth. Throughout his authorial career, and increasingly in his final years, Kierkegaard expresses concerns over what Johannes Climacus calls “the inadequacy of language.” Incited by Jesus's arsonist declaration “I came to cast fire upon the earth” (Luke 12:49), which he invokes as part of his attack on the established Danish Church, Kierkegaard becomes convinced that the “prolixities” of false Christendom “must go.” Yet, as his journals and authorship reveal, he remains haunted to the end of his life by thoughts about his (and his pseudonyms’) own sheer verbosity, his authorial needs for “filling up” time and narrative, and the ultimate “superficiality” of his literary vocation.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".