Bibliographic record
Abstract
Certaines images ont acquis une place particulière dans le « panthéon » de l’histoire de la photographie. Le portrait frontal de Sir John Herschel, réalisé par Julia Margaret Cameron en avril 1867, fait partie de ces rares spécimens qui, sans aucune discussion, doivent figurer dans les collections publiques et privées. Lors de la vente historique de Genève en 1961, l’image de l’illustre scientifique britannique atteint un prix record. Depuis, elle ne cesse de s’imposer comme la marque évidente du « talent » de l’autrice, incarnant la photographie comme volonté d’art. De quelles qualités intrinsèques ce portrait est-il doté, pour qu’il soit désormais considéré comme l’objet photographique parfait ? Référence ultime, il est une narration particulière, mise en place dès l’origine par la photographe elle-même, qui s’appuie, entre autres, sur cette image pour affermir sa réputation, c’est-à-dire son nom et son « œuvre ». Associé dorénavant à Cameron, le portrait de Herschel s’est installé définitivement dans le monde des biens de prestige, un univers restreint et univoque.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.006 |
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".