Poliesferas Pedagógicas: estudio analítico de las cosmologías locales del Covid-19
Bibliographic record
Abstract
Debido a la nueva realidad pandémica, nuestras aulas se han visto modificadas, pasando de un formato presencial al virtual. El fenómeno de compartir pantalla se ha convertido en el soporte de comunicación y expresión de vidas distintas que compartimos un mismo espacio virtual, separándonos físicamente tan sólo unos centímetros. Esta investigación observa la realidad experimentada y analiza la experiencia virtual de la la realidad espacial de nuestros nuevos entornos educativos. Para ello, se propone una metodología específica de análisis gráfico que permite examinar los espacios domésticos convertidos en docentes, ampliando el conocimiento sobre nuestras nuevas aulas físico-virtuales. El resultado es un atlas de poliesferas que recoge todos los objetos que nos acompañan virtualmente en nuestras pantallas, con el que se visibiliza la inversión de las estructuras clásicas de nuestras aulas, siendo ahora el mueble el centro de nuestra atención. Due to the new pandemic reality, our classrooms have been modified, evolving from on-site to online format. The screen sharing phenomenon is now the communication and expression medium of different lives which share the same virtual space, physically separated only by few centimeters. This research focuses on the experienced reality and analyzes the virtual experience of the spatial reality of our new educational environments. We propose an specific graphic analysis methodology which allows to examine the domestic spaces turned into academic spaces, expanding the knowledge about our new physical-virtual classrooms. The result is a polyspheres atlas that collects every object that we share virtually on our screens. This atlas visualizes the inversion of the classical structures of our classrooms, because the furniture or device is now the focus of our attention.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".