Proyecto a/r/tográfico para desarrollar investigación y práctica artísticas partiendo del texto-imagen
Bibliographic record
Abstract
Desarrollamos concretamente los marcos, teórico y metodológico, que sustentan la práctica educativa en Artes Visuales mediante Proyectos integrales que emplean imagen, texto y toda aquella documentación que despierte interés más allá de una obra gráfica. De este modo, el método de los cruzamientos amplía (no instruye) el horizonte que cada artista o investigador ponga a su trabajo. Tanto en los modelos transestético como holístico, reconocemos una línea joven de investigación que, nacida en Vancouver, va creando escuela conforme progresan sus prácticas experienciales. Aquí centramos la propuesta en los metalenguajes, que reaccionan críticos al logocentrismo tradicional, y permiten construir ideas propias partiendo de producciones también ajenas en lo que ya se ha descrito como `indagación vital´.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 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".