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Record W7070870609

Propuesta de Diagnostico Motivacional JRP para Emprendedores Textiles de MYPES Exportadoras Vinculadas a Promperú, Arequipa 2017 – 2020

2019· dissertation· es· W7070870609 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2019
Typedissertation
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)Quarter (Canadian coin)Limiting
DOInot available

Abstract

fetched live from OpenAlex

La presente investigación tiene como objetivo identificar los niveles de motivación que
\ntienen los emprendedores textiles de Mypes exportadoras al momento de iniciar su negocio
\nmediante un diagnostico motivacional.
\nPara la elaboración del estudio se utilizó una encuesta elaborada por José Ramón Pin, la cual
\nha sido adaptada para fines del caso y de esta manera recolectar la información necesaria.
\nUna vez hechas las encuestas al total de la muestra, se utilizaron programas como Excel y
\nSPSS para el procesamiento de la información, posteriormente se analizaron los datos
\nutilizando estadística descriptiva y por último se creó un cuadro de Baremo con cual se
\nidentificó el nivel de motivación que predomina en los emprendedores de nuestra
\ninvestigación.
\nSe llegó a la conclusión de que la motivación tiene un papel importante en nuestros
\nemprendedores encuestados, lo cual se verá reflejado a largo plazo, los resultados del estudio
\nindican que la motivación intrínseca, es aquella que predomina, luego le sigue la motivación
\ntrascendente y por el ultimo la motivación extrínseca, en este punto se debería trabajar para
\nque el total de los emprendedores tenga una motivación trascendente para que su negocio
\nperdure en el tiempo.
\n
\nPalabras Clave:
\n- Emprendedor
\n- Motivación
\n- Exportación

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.029
GPT teacher head0.254
Teacher spread0.225 · 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; both teacher heads agree on what is shown here.

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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