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Record W6998686538

Análise e gestão do risco: uma aplicação empírica à auditoria

2009· dissertation· pt· W6998686538 on OpenAlexfundno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2009
Typedissertation
Languagept
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsnot available
FundersArctic Goose Joint Venture
KeywordsAuditBusiness risksRisk managementStock exchangeSample (material)
DOInot available

Abstract

fetched live from OpenAlex

A análise e gestão do risco têm merecido nos últimos anos especial atenção por parte das organizações, que estão expostas regularmente a vários riscos de natureza interna e externa. O objectivo desta dissertação é salientar a importância da análise e gestão do risco para as organizações e para o trabalho desenvolvido no âmbito da auditoria, especialmente no que se refere ao desempenho organizacional. O estudo empírico incidiu sobre uma amostra constituída pelas empresas cotadas em mercado contínuo na Bolsa de Valores de Lisboa e pelas de Sociedades de Revisores Oficiais de Contas. A metodologia utilizada consistiu no envio de questionários com o objectivo de obter as informações necessárias para testar as hipóteses formuladas. Os resultados obtidos do estudo demonstram que as opiniões das empresas cotadas e das Sociedades de Revisores Oficiais de Contas face à importância da análise e gestão do risco nas organizações são semelhantes. - ABSTRACT: ln last years the analysis and management of risk has received special attention from those organizations that are usually exposed to internal and external risks. The purpose of this study is to underline the importance of analysis and management of risk for organizations and for audit work, especially concerning the organization performance. The empirical study is focused on a sample of Companies quoted on the Continuous Market of the Lisbon Stock Exchange and SROC' s. The methodology consisted on sending questionnaires in order to obtain the necessary information to test the hypotheses. The results show that the opinions of Companies and SROC's are similar concerning the importance of analysis and management of risk in organizations.

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)0.012
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0150.020
Science and technology studies0.0050.003
Scholarly communication0.0020.004
Open science0.0040.001
Research integrity0.0010.002
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 head0.051
GPT teacher head0.368
Teacher spread0.316 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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