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Record W2943749065

Tarifas telefónicas móviles y su incidencia en el costo de vida de los colombianos

2017· article· es· W2943749065 on OpenAlexaboutno aff
Gerson Eduardo Báez, Cesar Augusto Blanco

Bibliographic record

VenueRevista CONVICCIONES · 2017
Typearticle
Languagees
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyHumanitiesPolitical scienceWelfare economicsEconomicsArt
DOInot available

Abstract

fetched live from OpenAlex

ResumenEl proposito del presente trabajo es analizar el impacto financiero de las tarifas telefonicas moviles, en el costo de vida de los colombianos y compararla empresa internacional contra la nacional. La muestra estuvo representada por 7 paises, entre ellos: Mexico, Argentina, Espana, Estados Unidos, Canada, Australia y Colombia; los cuales fueron seleccionados por ser los mas representativos de este sector empresarial y por similitudes socioeconomicas. Se emplearon tecnicas estadisticas como la media, varianza, desviacion estandar y coeficiente de variacion para medir de manera efectiva el efecto en la economia. Los resultados obtenidos permitieron evidenciar que las empresas operadoras de servicios moviles manejan diferentes tarifas y servicios, siendo Estados Unidos el pais con las tarifas mensuales mas bajas y Canada la que posee la tarifa mensual mas alta, Mexico con tarifas intermedias y Colombia pese a que cuenta con los salarios minimos mas bajos, sus tarifas mensuales son altas comparadas con los paises estudiados. Se concluye que estas tarifas influyen de manera directa en la finanzas de las familias y que los paises con mayor impacto en la economia personal son: Mexico y Colombia respectivamente.Palabras Clave: Telefonia, Movil, Tarifas, Impacto,Financiero, Servicios, competitividad, cobertura.AbstractThe purpose of this paper is to analyze the financial impact of mobile telephone rates on the cost of living of Colombians and compare the international versus the national company. The sample was represented by 7 countries, among them: Mexico, Argentina, Spain, the United States, Canada, Australia and Colombia; which were selected for being the most representative of this business sector and for socioeconomic similarities. Statistical techniques were used such as the mean, variance, standard deviation and coefficient of variation to effectively measure the effect on the economy. The results obtained showed that mobile service operators handle different tariffs and services, with the United States being the country with the lowest monthly rates and Canada having the highest monthly rate, Mexico with intermediate rates and Colombia, despite having an with the lowest minimum wages, their monthlyrates are high compared to the countries studied. It is concluded that these rates directly influence the finances of families and that the countries withthe greatest impact on the personal economy are: Mexico and Colombia respectively.Keywords: Mobile, telephony, Charge, Finances, services, coverage, competitiveness, impact.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.498
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.014
GPT teacher head0.308
Teacher spread0.294 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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