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Record W3016672443 · doi:10.1136/bmjgh-2020-002325

Revolving doors and conflicts of interest in health regulatory agencies in Brazil

2020· article· en· W3016672443 on OpenAlexaff
Mário Scheffer, María Pastor‐Valero, Giuliano Russo, Ildefonso Hernández‐Aguado

Bibliographic record

VenueBMJ Global Health · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsInstitute of Population and Public Health
FundersMedical Research CouncilFundación CarolinaUniversidade Federal do Rio de JaneiroFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsDoorsPhenomenonRevolving doorPrivate sectorBusinessQuality (philosophy)Economic growthPolitical scienceEconomicsLawEngineering

Abstract

fetched live from OpenAlex

The 'Revolving Doors' phenomenon is both controversial and common worldwide, but little evidence exists from health sectors in low and middle-income countries (LMIC). We analyse the circulation of agents from regulatory to regulated entities in Brazil's two main health regulatory agencies. Almost half of the executives from such agencies in the last 20 years either started in or ended up working for the private health sector. We discuss paths and potential implications of such phenomenon for the quality of regulation of health markets in LMIC settings.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.663
GPT teacher head0.615
Teacher spread0.048 · 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 teacher head, 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

Citations8
Published2020
Admission routes1
Has abstractyes

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