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Record W3167671273 · doi:10.6000/1929-4409.2021.10.22

The Influence of Employee Competency in Small and Medium Business Brazil and Brics and Jair Bolsonaro’s 1st Year of Presidency

2021· article· en· W3167671273 on OpenAlexvenueno aff
Vasil Timerjanovich Sakaev, Tanya Yordanova Popova

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Industrial and Economic Development
Canadian institutionsnot available
FundersKazan Federal University
KeywordsLatin AmericansPresidencyPoliticsDemocracyIdeologyPolitical scienceEconomic historyPolitical economySociologyLawEconomics

Abstract

fetched live from OpenAlex

This study aims to look at employee competency with job satisfaction as an intervening variable at small and medium business (SMB) by consdring the Brazil politics. The political stage in Brazil changed course towards the “right” on 1 January 2019 when the anti-globalist former army officer Jair Bolsonaro was inaugurated as the 38th President of the Republic. That was an abrupt change of ideologies for a country leaded by the “left” (Workers’ Party) in the last 13 years. Scholars made contradictory assumptions about the future of BRICS: one of the most significant economic organisations on the international arena nowadays, within the new Brazilian background. In the beginning of 2019 the opportunity for Braxit was not excluded, although there was no immediate call for it. However, the most common opinion came from pragmatists like N. Muhandiram: they affirmed that the union would keep functioning but it would meet multiple challenges. This article gives an answer to the question why the “right” turn in Brazil affects the relations between the biggest Latin American democracy and BRICS.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.307
Teacher spread0.258 · 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 teacher head, 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
Published2021
Admission routes1
Has abstractyes

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