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A Função da Capacidade Dinâmica na Construção da Inovação Disruptiva: um Estudo de Caso da Primeira Empresa de Mediação 100% Online no Brasil

2018· article· pt· W4249844541 on OpenAlex
Mauricio José Da Silveira Júnior, Priscila Rezende da Costa, Lucas Daniel Ramos Ribeiro

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

VenueAmericanae (AECID Library) · 2018
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Este artigo tem o objetivo descrever o processo da criação da primeira empresa de mediação online do Brasil – Mediação Online (MOL) e as etapas do processo de mediação online de conflitos, como exemplo do uso da inovação como forma de desafogar o poder judiciário e estimular a solução rápida de lides, através do processo de mediação de conflitos num negócio digital. Através da sanção da lei 13.140/2015 a mediação foi regulamentada e este processo ganhou uma nova escala de eficiência com a aplicação das ferramentas de mediação através do uso da plataforma digital. Foi utilizado o método qualitativo de caráter exploratório, optando por um estudo de caso único através de entrevistas à fundadora e cofundadora, observação e avaliação documental. O artigo potencialmente contribui para demonstrar como o uso de algumas capacidades dinâmicas da empresa podem ser direcionadas para a construção da inovação disruptiva aplicadas ao negócio digital

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.005
Science and technology studies0.0010.006
Scholarly communication0.0010.003
Open science0.0040.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.065
GPT teacher head0.339
Teacher spread0.274 · 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