Estrategias de colaboración en el cluster biotecnológico del Discovery District de Toronto. El caso del proyecto MaRS
Bibliographic record
Abstract
En este ensayo se analiza un aspecto del desarrollo economico de Canada relacionado con la cooperacion e interaccion entre instituciones regionales a partir del concepto de sistemas de innovacion regional. El caso de estudio es el proyecto Medical and Related Science (MaRS), en el Discovery District de Toronto, enfocandose en el desarrollo de oportunidades dentro de una region de aprendizaje e innovacion interactiva y contribuyendo al fortalecimiento de los efectos de aglomeracion local, asi como a la creacion de nuevas interdependencias. En el ensayo se resaltan los determinantes politicos y economicos de un desarrollo industrial exitoso, centrandose en la creacion de redes (networking) entre gobierno, instituciones, empresas y organizaciones publicas y privadas de I+D, el fomento de un crecimiento industrial sostenido y de mayor competitividad nacional e internacional. Estos elementos sirven de marco para explicar por que Canada se ha colocado como lider en firmas biotecnologicas y que el area metropolitana de Toronto (GTA) albergue el cluster medico y biotecnologico mas grande en Norteamerica
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".