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Sistema de información de mercado para el sector de agroalimentos de los mercados de la provincia de Tungurahua

2018· article· es· W3010095347 on OpenAlexvenueno aff
Yolanda Tatiana Carrasco Ruano

Bibliographic record

VenueConcienciaDigital · 2018
Typearticle
Languagees
FieldSocial Sciences
TopicSocial Issues and Policies in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

El ingreso de un bachiller a una universidad es un escalón más para seguir superándose, alcanzar sus sueños, metas o deseos para que en un futuro pueda tener una vida tranquila y prospera a lado de sus seres queridos, pero si esta meta se ve truncada porque la universidad está muy lejos y no cuenta con los recursos necesarios para aprovechar esa oportunidad. Es por eso que el objetivo de este trabajo es explorar si la migración interna que se da en nuestro país para poder ingresar a la educación superior por parte de los jóvenes bachilleres, puede ser representada como un factor de riesgo en los ámbitos sociales, económicos y de salud. Se diseñó una investigación deductiva, observacional y de comparación propia de todos los factores positivos y negativo que se reflejan en este problema social, en mi caso soy parte de este gran círculo problemático donde yo he tenido problemas tanto económicos como familiares para conllevar mis estudios superiores pero con la ayuda de personas que me aprecian he podido seguir estudiando y sé que muchos jóvenes con el mismo problema migratorio que yo han debido abandonar los estudios o recurren al consumo de estupefacientes por no saber cómo afrontar el no seguir estudiando o no contar con el apoyo de sus allegados y es ahí donde esta investigación tratara de juntar todos los factores que truncan a un estudiante a salir adelante, sobresalir y acabar su carrera universitaria.

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)0.011
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 score0.107
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.017
GPT teacher head0.380
Teacher spread0.362 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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