Bibliographic record
Abstract
La noción de open science no sólo tiene que conjugar todas las formas de dar acceso (papers, data y notebooks), sino también las de promover participación, ya sea incentivando la colaboración entre una heterogeneidad de actores (science shops, citizen panels, consensus conferences, participatory action-research, living labs, hackerspaces, laboratorios ciudadanos, design assemblies) ya sea expandiendo el diálogo de saberes y haciendo más porosas las fronteras entre la academia y la urbe, los expertos y los amateurs, el conocimiento de laboratorio y el de campo, el aula y la plaza o el experimental y el experiencial. Abrir la ciencia también involucra el diseño de infraestructuras que garanticen la soberanía de la comunidad científica, como también abrir el ecosistema o, en otros términos, problematizar los protocolos que regulan la evaluación, financiación y licencia de la investigación, como también la gobernanza de la vida académica, incluidas las convocatorias y los jurados, o los premios, concursos, comisiones y, desde luego, los dispositivos de planeación.
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 | 0.038 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.014 | 0.068 |
| Scholarly communication | 0.042 | 0.035 |
| Open science | 0.004 | 0.030 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.022 | 0.008 |
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".