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Record W3168642249 · doi:10.46589/rdiasf.vi34.357

El impacto de la crisis sanitaria generada por COVID-19 en la finanzas de las Pequeñas y medianas empresas (Pymes) de Hermosillo, Sonora.

2021· article· es· W3168642249 on OpenAlex
Martín Durán Acosta

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista de Investigación Académica Sin Frontera División de Ciencias Económicas y Sociales · 2021
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyCartographyArt

Abstract

fetched live from OpenAlex

Resumen Esta investigación, por diseño, es de tipo descriptiva y exploratoria y su objetivo es determinar, a partir de la apreciación que tienen los gerentes o responsables de la gestión financiera de las Pymes, como impacta a sus finanzas la crisis de salud ocasionada por el COVID-19 para el desarrollo e inverción de sus negocios. Los resultados obtenidos en la investigación muestran que la crisis de salud provocada por el COVID-19 ha sido un desafío para las Pymes porque ha generado una fuerte crisis, pero se han mostrado cautelosas en las medidas para enfrentarla, y las estrategias de gestión financiera orientadas a evitar el endeudamiento. En conclusión, la gerencia de las Pymes es consciente de que para afrontar la nueva modalidad es necesario realizar una gestión administrativa y financiera basadas en estrategias previsibles, teniendo en cuenta los cambios encaminados al desarrollo e inversión de sus negocios.

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.

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)0.007
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.294
Teacher spread0.252 · 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