Bibliographic record
Abstract
Cet article se penche sur une série de photographies prises par Eli Lotar lors d’un voyage avec son collègue photographe Jacques-André Boiffard à bord de l’Exir Dallen, un voilier appartenant à un ingénieur industriel nommé Fernando de Cárdenas. Rejoignant le groupe de Cárdenas alors que le navire se dirigeait de l’Espagne vers l’Afrique du Nord en 1933 et 1934, les photographes documentèrent les populations pauvres vivant le long des côtes des deux continents. À cette époque, Lotar et Boiffard s’étaient engagés dans la politique communiste et participaient aux activités de l’Association des écrivains et artistes révolutionnaires (AEAR). En analysant ces photos en relation à la critique de l’AEAR de l’intervention franco-espagnole au Maroc, je soutiens que la série Exir Dallen était une tentative pour mobiliser la photographie au service de politiques anticoloniales et antifascistes. Ce faisant, je remets en cause un récit commun en histoire de l’art qui met les deux photographes presque exclusivement en rapport avec le surréalisme.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".