Bibliographic record
Abstract
En 1973, Paul Simon chantait : « Kodachrome/They give us those nice bright colors/They give us the greens of summers/Makes you think all the world’s a sunny day. » Le premier titre de cette chanson, Kodachrome , était Going Home . Qu’est-ce qui explique cette affinité entre le motif du « retour à la maison » et le nom de la célèbre pellicule commercialisée par Kodak en 1935 ? Quel est le sentiment de nostalgie, de familiarité poignante , que ce mot évoque et qui semble indissociable des qualités chromatiques particulières du film, ses couleurs vives et saturées ? Cet article, construit comme une mosaïque ou un montage de fragments juxtaposés, puise tant dans l’histoire de la pellicule que dans des souvenirs personnels pour faire un portrait de ses usages et de ses imaginaires, passés et contemporains. Il cherche à faire apparaître les différentes déclinaisons de ce mot, Kodachrome, et les multiples facettes de la nostalgie qu’il mobilise.
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 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".