Encouraging the use of generic medicines: implications for transition economies.
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.
Bibliographic record
Abstract
Generic drugs have a key role to play in the efficient allocation of financial resources for pharmaceutical medicines. Policies implemented in the countries with a high rate of generic drug use, such as Canada, Denmark, Germany, the Netherlands, the United Kingdom, and the United States, are reviewed, with consideration of the market structures that facilitate strong competition. Savings in these countries are realized through increases in the volume of generic drugs used and the frequently significant differences in the price between generic medicines and branded originator medicines. Their policy tools include the mix of supply-side measures and demand-side measures that are relevant for generic promotion and higher generic use. On the supply-side, key policy measures include generic drug marketing regulation that facilitates market entry soon after patent expiration, reference pricing, the pricing of branded originator products, and the degree of price competition in pharmaceutical markets. On the demand-side, measures typically encompass influencing prescribing and dispensing patterns as well as introducing a co-payment structure for consumers/patients that takes into consideration the difference in cost between branded and generic medicines. Quality of generic medicines is a pre-condition for all other measures discussed to take effect. The paper concludes by offering a list of policy options for decision-makers in Central and Eastern European economies in transition.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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