Análisis del sector de los e-sports
Bibliographic record
Abstract
Como consecuencia de la gran actualidad de los e-sports, se crea este \ntrabajo, con la intención de dar a conocer el sector, pero, sobre todo, \nentender cómo funciona y hacer un análisis estratégico sobre el mismo, \nentendiendo las relaciones entre los agentes implicados, y buscando las \namenazas y debilidades que presenta. Para ello, se utilizarán los \nconocimientos y gustos que presento como espectador del sector, así como \ntécnicas y herramientas de análisis empleadas ampliamente en la dirección \nestratégica de las empresas, con el fin de determinar cómo opera el sector, \nlas relaciones que existen entre los distintos agentes, cómo las \nparticularidades del sector influyen sobre las acciones de los agentes, y por \núltimo detectar esas amenazas y oportunidades tan características de los \nanálisis DAFO.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".