Russek, Dan. Textual Exposures. Photography in Twentieth-Century Spanish American Narrative Fiction. Calgary: University of Calgary Press, 2015.
Bibliographic record
Abstract
¿Ha muerto la fotografía, como medio y como arte?Nos encontramos en un periodo postfotográfico, dominado por la imagen digital y su gramática de píxeles.Cuando hablamos de fotografía, ciertos vocablos se reconocen ya como restos de un léxico casi extinto o exclusivo, tocado por la nostalgia y su prestigio: "película", "revelado", "cuarto oscuro", son palabras que remiten a otro tiempo, una era de glamour en blanco y negro, y están, además, asociadas a la imagen fotográfica en su dimensión perdida de objeto, de talismán sometido al tacto, el afecto y la temporalidad, que hoy, desmaterializado, subsiste como realidad virtual.Por ello sostiene Dan Russek en este sugerente libro que el atractivo actual de la fotografía para la imaginación literaria, su capacidad de seguir inspirando y dando forma a las narraciones del futuro, están ligados al pasado y la historia (156), y a esa promesa de revelación visual que le permitió a este arte mantener una conversación privilegiada con los mayores exponentes de la literatura hispanoamericana del siglo XX.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".