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Record W3089413491 · doi:10.31876/ie.v2i3.24

O impacto do treinamento em gestão para a promoção do turismo através do desenvolvimento de vinhedos

2019· article· pt· W3089413491 on OpenAlexaff
Josefa B. da Silva

Bibliographic record

VenueRevista Iberoamericana de la Educación · 2019
Typearticle
Languagept
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

A pesquisa tem como objetivo analisar os fatores que geraram a taxa de desemprego em egressos da Faculdade de Ciências Administrativas da Universidade de Guayaquil. O objetivo deste trabalho é saber se existe uma relação entre o desemprego e a formação recebida na Universidade de Guayaquil; portanto, foi realizado um estudo focado nas atividades que esses graduados estão atualmente realizando; através de pesquisa quantitativa, através de métodos empíricos, como pesquisas aplicadas a graduados. Como resultado, foi possível determinar que uma grande porcentagem não tem emprego, pois o principal fator de influência é o desemprego cíclico devido à fraca economia do país. Em conclusão, propõe-se projetar e executar uma proposta que a Universidade de Guayaquil implementaria com um programa de capital semente como estratégias de empreendedorismo com estratégias inovadoras, a fim de diminuir a taxa de desemprego de graduados da Faculdade de Ciências Administrativas na carreira de Engenharia Comercial.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.018
GPT teacher head0.262
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2019
Admission routes1
Has abstractyes

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