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Privatização: bom ou ruim? Lições do setor de distribuição de energia elétrica do nordeste brasileiro

2010· article· pt· W2000268142 on OpenAlex

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

VenueRevista de Administração de Empresas · 2010
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPolitical sciencePhysicsComputer science

Abstract

fetched live from OpenAlex

Este trabalho analisa a evolução de cinco distribuidoras de energia elétrica, localizadas no Nordeste do Brasil, por meio de indicadores técnicos e financeiros. Três empresas privatizadas e duas públicas foram analisadas entre 1997 e 2008. Os indicadores financeiros mostram a lucratividade e capacidade de as firmas gerarem valor para os acionistas, enquanto os técnicos a qualidade do serviço prestado aos consumidores. Duas proposições foram estabelecidas sugerindo que as empresas privatizadas tiveram seus indicadores financeiros e técnicos melhorados, comparativamente às empresas públicas, depois da privatização. Observou-se que os indicadores financeiros das distribuidoras privatizadas melhoraram em relação aos das públicas, gerando mais valor para seus acionistas. No entanto, não há evidência de que a privatização impactou na melhoria dos indicadores técnicos e qualidade do serviço.

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)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.370
Teacher spread0.314 · 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