Corporate social responsibility to improve access to medicines: the case of Brazil
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Access to medicines and the development of a strong national pharmaceutical industry are two longstanding pillars of health policy in Brazil. This is reflected in a clear emphasis by Brazil's Federal Government on improving access to medicine in national health plans and industrial policies aimed at promoting domestic pharmaceutical development. This research proposes that such policies may act as incentives for companies to pursue a strategic Corporate Social Responsibility (CSR) agenda. CSR that supports Governmental priorities could help companies to benefit significantly from the Governmental industrial policy. We sought to determine whether CSR activities of Brazilian pharmaceutical firms are currently aligned with the Federal Government's health prioritization. To do so we examined key Brazilian health related policies since 2004, including the specific priorities of Brazil's 2012-2015 Health Plan, and compared these with CSR initiatives that are reported on the websites of select pharmaceutical firms in Brazil. RESULTS: Brazil's national health plans and industrial policies demonstrated that the Federal Government has followed diverse approaches for improving access to medicines, including strengthening health care infrastructure, increasing transparency, and supporting product development partnerships. Case studies of six pharmaceutical firms, representing both public and private companies of varying size, support the perspective that CSR is a priority for firms. However, while many programs target issues such as health infrastructure, health care training, and drug donation, more programs focus on areas other than health and do not seem to be connected to Governmental prioritization. CONCLUSION: This research suggests that there are loose connections between Governmental priorities and pharmaceutical firm CSR. However, there remains a significant opportunity for greater alignment, which could improve access to medicines in the country and foster a stronger relationship between the Government and industry.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it