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Record W2091703239 · doi:10.1186/1471-2458-14-63

Why the MDGs need good governance in pharmaceutical systems to promote global health

2014· article· en· W2091703239 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

VenueBMC Public Health · 2014
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCorporate governanceGood governanceLanguage changeMillennium Development GoalsPublic healthPopulation healthCitizen journalismPopulationContext (archaeology)Public relationsMedicinePublic administrationBusinessEconomic growthPolitical scienceDeveloping countryEconomicsEnvironmental healthLawFinance

Abstract

fetched live from OpenAlex

BACKGROUND: Corruption in the health sector can hurt health outcomes. Improving good governance can in turn help prevent health-related corruption. We understand good governance as having the following characteristics: it is consensus-oriented, accountable, transparent, responsive, equitable and inclusive, effective and efficient, follows the rule of law, is participatory and should in theory be less vulnerable to corruption. By focusing on the pharmaceutical system, we explore some of the key lessons learned from existing initiatives in good governance. As the development community begins to identify post-2015 Millennium Development Goals targets, it is essential to evaluate programs in good governance in order to build on these results and establish sustainable strategies. This discussion on the pharmaceutical system illuminates why. DISCUSSION: Considering pharmaceutical governance initiatives such as those launched by the World Bank, World Health Organization, and the Global Fund, we argue that country ownership of good governance initiatives is essential but also any initiative must include the participation of impartial stakeholders. Understanding the political context of any initiative is also vital so that potential obstacles are identified and the design of any initiative is flexible enough to make adjustments in programming as needed. Finally, the inherent challenge which all initiatives face is adequately measuring outcomes from any effort. However in fairness, determining the precise relationship between good governance and health outcomes is rarely straightforward. SUMMARY: Challenges identified in pharmaceutical governance initiatives manifest in different forms depending on the nature and structure of the initiative, but their regular occurrence and impact on population-based health demonstrates growing importance of addressing pharmaceutical governance as a key component of the post-2015 Millennium Development Goals. Specifically, these challenges need to be acknowledged and responded to with global cooperation and innovation to establish localized and evidence-based metrics for good governance to promote global pharmaceutical safety.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
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 head0.120
GPT teacher head0.440
Teacher spread0.320 · 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