Bibliographic record
Abstract
I f you have visited Rome, you have probably walked these streets, although they no longer exist. The grubby, lowlife quartiere alessandrino, a neighborhood of ageless, crumbling buildings made into cheap flats and hotels to accommodate Rome’s booming immigrant and transient population, once stood where today’s tourists mass and traffic roars between the Coliseum and the Vittorio Emanuele Monument. As one of his great building projects, Mussolini had the quarter razed in the 1930s to create a triumphal passageway, the Via dellTmpero, through the ruins of empire leading to his balcony over Piazza Venezia, the mighty platform from which he urged his people on to glory and disaster. 1 Five thousand five hundred habitable units were destroyed, three churches were pulled down, and 85 percent of five recently uncovered ancient forums were re-covered by roadway, all to provide a ceremonial backdrop to the Duce’s ambitions. 2 The seven thousand displaced inhabitants of the quarter were relocated to prefab houses on the city’s outskirts, which later became notorious in their own right as the borgate , the desolate setting for the early novels of Pier Paolo Pasolini, focused on the unconquerable, anarchic vitality of the poor. 3 These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.089 | 0.019 |
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".