Bibliographic record
Abstract
And if your kids don’t study, that’s your fault. Tell ’em. Don’t kid yourself, and don’t lie. (xcix/725) “ Il nemico è l'ignoranza ”: Ezra Pound's daughter Mary de Rachewiltz once identified this terse proposition as her father's “slogan” in the years prior to World War II. It can no less reasonably be understood as a lifelong maxim, an ideal instance of the “gists and piths” ( ABCR , 92) that motivated and moved the poet, and did so long before he formulated that memorable phrase. Pound's unwobbling belief that “not knowing” is the real enemy gestures with appropriate force and emphasis to the twin functions of “to educate,” from a verb suggesting both “to bring up” ( educare ) and “to lead out” ( educere ). That is to say, it invests education with an urgency that applies equally to the family and the polity, one which may be extended without distortion to an ethical responsibility for all serious artists ( aliter : “the damned and despised litterati ”) ( LE , 21). During the 1920s Pound concluded that “[t]he aim of state education has been (historically) to prevent people from discovering that the classics are worth reading” ( SPR , 213). In response, as he became increasingly remote from the centers of culture and higher learning, his pedagogical rhetoric became increasingly concerned with the idea that “the mental life of a nation is no man's private property. The function of the teaching profession is to maintain the health of the national mind ” ( LE , 58).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.388 | 0.210 |
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".