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Record W1976990156 · doi:10.1177/0275074010380449

Management Innovation at the Brazilian Superior Tribunal of Justice

2010· article· en· W1976990156 on OpenAlexaff
Tomás de Aquino Guimarães, Catarina Cecília Odelius, Janann Joslin Medeiros, João Augusto Vargas Santana

Bibliographic record

VenueThe American Review of Public Administration · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsTribunalWork (physics)Economic JusticeBusinessKnowledge managementProcess (computing)Public relationsProcess managementPublic administrationPolitical scienceSociologyLawComputer scienceEngineering

Abstract

fetched live from OpenAlex

We describe administrative reform involving management innovation undertaken at the Superior Tribunal of Justice, Brazil’s highest appellate court for infra-constitutional cases. The innovation is the introduction of a new management model based on strategic planning and a process management approach to work processes. Introduction of the new model has been supported by the use of information technology and project management techniques. Qualitative methods were used for data collection and analysis. Findings reveal that the innovation is contributing to the development of a systemic overview of key processes, reducing the fragmenting effects of the division of work activities within the Tribunal. At least three new organizational routines or capabilities have been developed as a result of the innovation studied: Electronic Court Management, Project Management, and Process Management. The paper contributes to knowledge about court management, a field that has received little research attention in the public administration literature.

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)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0140.010
Scholarly communication0.0060.002
Open science0.0010.006
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.281
Teacher spread0.263 · 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 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

Citations36
Published2010
Admission routes1
Has abstractyes

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