Competitividad de las tortillerías de la ciudad de Tijuana B.C. México frente al COVID-19
Bibliographic record
Abstract
La presente investigación busca analizar los factores externos que influyen enla competitividad de las tortillerías de la ciudad de Tijuana, Baja California, México; mediante la aplicación de dos modelos de competitividad: las 5 fuerzas dePorter y competitividad sistémica, el diseño de esta investigación fue de corte transversal utilizando el método cualitativo descriptivo, tomando datos del periodo 2020 debido a la crisis sanitaria de covid-19 en México. el sujeto de estudio está conformado por un total de 296 tortillerías de la ciudad de Tijuana, Baja California, México. Los principales resultados indican que el sector tortillero tiene aspectos que fortalecer para generar ventajas competitivas, otros resultados mostraron que las mipymes manufactureras de tortillerías de Baja California son medianamente competitivas con tendencia importante hacia la baja ya que los factores externos analizados presentan niveles de competitividad de medio a bajo.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".