Bibliographic record
Abstract
Abstract Conservative Circuits traces the careers of literary intellectuals associated with William F. Buckley, Jr.’s National Review. Between the 1950s and 1980s, writers and critics like Whittaker Chambers, John Dos Passos, Hugh Kenner, Guy Davenport, Joan Didion, Garry Wills, and D. Keith Mano helped make Buckley’s version of conservatism respectable. In Buckley’s magazine and in their better-known books, they fashioned a body of literary work that takes up and refracts right-wing concerns about tradition, religion, and personal liberty. They helped conservatives present themselves as a counter-elite sheltering traditional, humanities-based knowledge within a technocratic welfare state. In so doing, they facilitated the magazine’s assault on the very possibility of expertise, ushering in the fragmented media landscape that has characterized the United States since the late 1960s.
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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.022 | 0.036 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.323 | 0.269 |
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".