Jean Paul Gaultier: Diversidad e Inclusión
Bibliographic record
Abstract
Hoy los temas de diversidad e inclusión están en casi todas las agendas mundiales sean políticas, sociales o económicas. Eso es porque el mundo avanza, no siempre a la velocidad ideal, pero avanza hacia una proclamación de los derechos humanos planetaria con la intrínseca idea de que los humanos somos todos sin distinción de origen, color, raza, sexo o religión. Claro que dependiendo del lugar del planeta donde vivamos hay diferencias en cómo nuestros derechos son respetados. En Paris y en el sector de la moda y desde los años ochenta Jean Paul Gaultier levanta la bandera de la diversidad y la inclusión. ¿Una utopía o un mensaje social muy fuerte de alto impacto? Su trayectoria es ejemplar en estos temas y de eso se trata este artículo.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 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".