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Auditoria Arquivística: uma proposta de requisitos

2019· article· pt· W2942722048 on OpenAlexaff
Danielle Alves Batista, Eliane Braga de Oliveira

Bibliographic record

VenueInformação & Sociedade Estudos · 2019
Typearticle
Languagept
FieldSocial Sciences
TopicBrazilian Legal Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhilosophyHumanities

Abstract

fetched live from OpenAlex

Estudo sobre auditoria arquivística onde discutem-se os conceitos de auditoria, arquivística e gestão de documentos. Discorre sobre a gestão de documentos na administração pública com ênfase na informação orgânica e no patrimônio público documental, bem como sobre a fiscalização da gestão de arquivos públicos com o objetivo de propor requisitos básicos para a realização de auditoria arquivística. As técnicas para coleta de dados são a pesquisa bibliográfica e a pesquisa documental. Realiza uma análise comparativa entre os requisitos identificados na literatura de auditoria, relaciona-os com a Legislação Arquivística Brasileira e as recomendações de três autores da disciplina arquivística: Antonia Heredia Herrera, Heloisa Liberalli Belotto e Theodore R. Schellenberg. Os resultados são uma proposta de requisitos básicos para a auditoria arquivística e a identificação das contribuições da auditoria às funções arquivísticas. Concluiu-se que a auditoria arquivística pode contribuir para o aprimoramento da gestão pública e da formação do patrimônio cultural brasileiro.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.036
metaresearch head score (Gemma)0.095
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.095
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0210.017
Science and technology studies0.0060.014
Scholarly communication0.0180.017
Open science0.0030.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.321
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations4
Published2019
Admission routes1
Has abstractyes

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