El impacto de la crisis sanitaria generada por COVID-19 en la finanzas de las Pequeñas y medianas empresas (Pymes) de Hermosillo, Sonora.
Bibliographic record
Abstract
Resumen Esta investigación, por diseño, es de tipo descriptiva y exploratoria y su objetivo es determinar, a partir de la apreciación que tienen los gerentes o responsables de la gestión financiera de las Pymes, como impacta a sus finanzas la crisis de salud ocasionada por el COVID-19 para el desarrollo e inverción de sus negocios. Los resultados obtenidos en la investigación muestran que la crisis de salud provocada por el COVID-19 ha sido un desafío para las Pymes porque ha generado una fuerte crisis, pero se han mostrado cautelosas en las medidas para enfrentarla, y las estrategias de gestión financiera orientadas a evitar el endeudamiento. En conclusión, la gerencia de las Pymes es consciente de que para afrontar la nueva modalidad es necesario realizar una gestión administrativa y financiera basadas en estrategias previsibles, teniendo en cuenta los cambios encaminados al desarrollo e inversión de sus negocios.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".