Asociatividad de productores de la región norte que permita la exportación de arándano fresco a Ontario – Canadá, Trujillo - 2017
Bibliographic record
Abstract
ABSTRACT \n \nNowadays, blueberries are captivating several consumers because of their natural \nproperties. This trend is reflected in the export growth figures of Trade Map, which show a \nsustained increase of 13.59% in the last 5 years. In contrast, in Northern Peru we find \nproducers of blueberries, who due to their limited availability of hectares for sowing, nonstandardized \nproduction \nand \nrestrictive \nbusiness \ncontact, \nthey \ncan’t \nbe \nable \nto \nproduce \non \n \na \nlarge \nscale \nin \norder \nto \nimprove \ntheir \ncompetitiveness \nin \nthe \nmarket. \n \n \n \nThese \n \nproducers will have possibility of accessing the international market through the \ndevelopment of differential strategies which can promote growth and permanence in the \nlong term. In the face of these globalization challenges, well-designed associative \nbusiness models of small and medium-sized producers appear as a competitive strategy \nto increase business efficiency and effectiveness. \n \nBusiness Association generates dynamism which allows to implement a solid network in \norder to exchange resources and technology, to obtain short productive cycles, to achieve \neconomies of scale, to improve level of negotiation, to achieve internationalization of the \nthese producers and to eliminate intermediation effect which is the main problem of the \nmajority of producers. \n \nAs described above, the present research is developed with the aim of proposing that the \nformal blueberry producers of the Northern Region of Peru to be part of a mechanism of \nAssociativity as a competitive tool which allows to enter to international markets.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".