Evaluación del impacto de corto plazo de SENACYT en la innovación de las empresas panameñas
Bibliographic record
Abstract
El presente documento presenta una evaluación preliminar del impacto que el programa de subvenciones a la investigación y desarrollo tiene en la dinámica innovadora de las firmas panameñas. Dentro de las limitaciones de los escasos datos disponibles, la metodología resuelve el problema de la atribución mediante el empleo de métodos cuasi-experimentales. El ejercicio hace uso de información nueva contenida en la reciente encuesta de innovación de Panamá, conjuntamente con información de registro de las firmas beneficiadas. Lamentablemente, dado el corto horizonte temporal disponible para la evaluación, solamente resultados de corto plazo han podido ser monitoreados. Dentro de estas limitaciones, se encuentra que las empresas beneficiarias han sistemáticamente incrementado su esfuerzo innovador y que ello se ha visto reflejado en un aumento en la incidencia de invención tecnológica a un nivel precompetitivo.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".