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Record W1886071082 · doi:10.17524/repec.v9i3.1176

A divulgação do risco nas demonstrações financeiras: uma análise ao anexo das sociedades não financeiras portuguesas

2015· article· pt· W1886071082 on OpenAlexaff
Maria De Lima e Silva, Fábio Albuquerque, Manuela Marcelino, Joaquín Texeira Quirós

Bibliographic record

VenueRevista de Educação e Pesquisa em Contabilidade (REPeC) · 2015
Typearticle
Languagept
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

O presente estudo tem por objetivo analisar a divulgação do risco efetuada por parte das sociedades não financeiras Portuguesas cotadas na Euronext de Lisboa ao longo dos anos de 2011 e 2012. Foram analisadas as características da informação divulgada em matérias ligadas ao risco tendo em conta o âmbito temporal, o caráter quantitativo ou qualitativo da informação, a natureza e a classificação do risco divulgado. Os dados para este estudo foram recolhidos a partir da análise de conteúdo ao anexo dos relatórios e contas (contas consolidadas) das entidades pertencentes à população durante o período de 2011 e 2012, resultando numa população de 36 entidades. Os referidos dados foram posteriormente submetidos a técnicas de análise univariada e bivariada baseada em testes não paramétricos, nomeadamente o teste de Wilcoxon. Os resultados demonstram que predomina a divulgação de informação financeira de forma qualitativa, referente ao passado e classificada como “boas notícias”. Pretende-se que os resultados desta investigação possam contribuir para a compreensão do tema desenvolvido, como é o caso dos elementos que se encontram na base da divulgação de informação de matérias ligadas ao risco.

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)0.005
metaresearch head score (Gemma)0.006
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), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0040.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.003

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 head0.034
GPT teacher head0.285
Teacher spread0.251 · 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 designNot applicable
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

Citations5
Published2015
Admission routes1
Has abstractyes

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