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.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 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".