Construyendo una metodología para la evaluación del riesgo en actividades agrícolas y agroindustriales en Bolivia que no cotizan en bolsa
Bibliographic record
Abstract
Se presenta una metodologia de evaluacion de riesgo empresarial que consiste en la identificacion de los factores causantes de los indicadores de riesgo tradicionalmente observados. Esta metodologia permite el calculo de ponderaciones objetivas para estas causas a fin de compararlas, jerarquizarlas y facilitar la toma de decisiones por parte de inversionistas. Esta metodologia se inscribe en el proyecto Sociedades de Transformacion Rural financiado por el International Development Research Center (IDRC) del Canada y el Fondo Internacional para el Desarrollo Agricola (FIDA), co-ejecutado por Centro de Investigacion para el Desarrollo Regional (CIDRE), la Universidad Privada Boliviana (UPB) y la Fundacion Valles, constituyendose en una herramienta alternativa de medicion de riesgo empresarial en Bolivia, especificamente disenada para brindar la posibilidad de inclusion de empresas agricolas y agroindustriales sobresalientes en el dinamismo del mercado de financiamiento directo del pais, generando desarrollo sostenible e inclusivo. El documento presenta en detalle los fundamentos teoricos y metodologicos de esta nueva propuesta, ademas de aplicaciones empiricas en dos sectores economicos de alta relevancia social para Bolivia: el sector agricola y el sector agroindustrial.
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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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".