La evolución del concepto marca país en el modelo de promoción global canadiense
Bibliographic record
Abstract
El entorno internacional ha determinado en los ultimos anos un mejor posicionamiento a aquellos productos y servicios que estan fuertemente respaldados en el mercado por una marca que los diferencia y que son sinonimo de calidad. Las naciones del mundo –como destinos de inversion– tambien han sufrido este fenomeno de mercadeo y han comenzado a profundizar en su diferenciacion a traves de la construccion de una imagen e identidad que facilite su posicionamiento internacional. Canada ha sido una de las naciones vanguardistas en el desarrollo de acciones coordinadas en torno a la ejecucion de una estrategia de marca pais. Recientemente se ha distinguido por el logro de multiples beneficios, evidenciados en la productividad y estimulacion de su economia, lo que avala el gran alcance de este proposito al que cada dia se unen mas naciones. La Estrategia de Marca Pais busca lograr que a traves de las caracteristicas mas resaltantes de una nacion, como pueden ser sus recursos naturales, productos, servicios y costumbres, se pueda crear una imagen que influya positivamente en la percepcion que se tiene de esta en el extranjero
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".