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Record W2961646588

Asociatividad de los productores de textiles artesanales de la provincia de San Miguel-Cajamarca para promover su exportación al mercado canadiense, 2020

2018· dissertation· es· W2961646588 on OpenAlexaboutno aff
María Fernanda Díaz del Castillo, Mayra Yoseline García Mejía

Bibliographic record

VenueUniversidad Privada del Norte · 2018
Typedissertation
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsProduct (mathematics)BusinessSupply and demandTextileGeographyTarget marketEconomyMarketingEconomicsMathematicsArchaeology
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT The purpose of this thesis was to seek the associativity of artisan textile producers in the province of San Miguel in the city of Cajamarca to promote its export to the Canadian market, identifying the most attractive markets and the most suitable for the export of these products, knowing its offer and current demand and thus expose the proposals for improvement to generate the associativity A non-experimental and descriptive research was carried out; using data collection techniques such as interviews which were applied to the presidents of the associations and to each one of its members, to know the process of elaboration of their products and to identify if they have an exportable offer. A documentary review was also carried out to generate the study of the Canadian market, which allowed to determine and analyze the demand of textile products in this country. As a result of the study carried out, it was determined that through associativity a greater exportable supply can be generated, as well as searching for more destination markets to internationalize the product. On the other hand, a series of recommendations were proposed, which are aimed at encouraging the growth of this sector not only in the province of San Miguel but also in the other provinces of the Department of Cajamarca.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.235
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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