Bibliographic record
Abstract
Habitant des pays d'Oc, méridional mon frère, tu le sais que nous sommes tous riches et musiciens? Riche en mots et musiciens de phrases. Claude Marti, Sol y sombra In 1996 two books on the troubadours appeared, both substantial studies, both the product of over a decade of research, and both offering an in-depth look at individual figures, their music and its sources. Yet each presented a different point of view. Elizabeth Aubrey's The Music of the Troubadours described and inventoried manuscript sources, transcribed melodies either in a rhythmically neutral notation or in an approximation of medieval note shapes, and described their tonal characteristics. It was the product of a well-established German-American academic study of both the troubadours and medieval music, and copies would quickly find their way on to college and university library shelves; it was recently reissued in a paperback edition. Gérard Zuchetto's Terre des troubadours was a view of the troubadours from one of their descendants, a singer-composer and native Occitan speaker born and bred in the Languedoc who had founded an international centre for troubadour research. His book was a luxurious coffee-table edition twice the weight of Aubrey's tome, with colour illustrations on nearly every page – a book partly funded by the Languedoc-Roussillon region and little known in North America.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.152 | 0.033 |
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".