« Like short movies in my head » : les mondes narratifs dans les musiques populaires
Bibliographic record
Abstract
I love songs where I can see a movie from the lyrics 1 Like short movies in my head : les mondes narratifs dans les musiques pop... Cahiers de Narratologie, 41 | 2022 1 la cration de mondes narratifs travers leurs paratextes et diverses extensions mais aussi travers la simple coute -qui reste centrale dans le cas de musiques dont le support phonographique permet un haut niveau de dtail et ouvre donc la voie de nombreuses formes d'coute immersive. Ce concept de monde narratif est ici emprunt la narratologie cognitiviste : il ne s'agit pas de mondes intgralement conus par les auteurs des albums, mais de mondes reconstitus et complts par les auditeurs partir des lments perus lors de l'coute et de la dcouverte de l'album 4 . Ce phnomne n'est pas systmatique, mais constitue un des possibles facteurs d'immersion dans un objet reu comme un rcit.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".