Orphan drug policies: implications for the United States, Canada, and developing countries.
Bibliographic record
Abstract
The United States’ Orphan Drug Act (“ODA”) has been hailed as “one of the most successful US legislative actions in recent history”. Although many countries, and governing bodies, have enacted Orphan Drug legislation in the past decade, the United States (US) was the first country to implement an official policy, primarily because of public pressure due to the lack of treatment options for rare disease sufferers in the US. For everyone who has espoused the virtues of the ODA in encouraging research into rare disease treatments, there are equal numbers of detractors who claim that it is a policy that serves mainly to promote private industry by allowing companies to charge outrageous prices for products that rare disease sufferers have no option but to purchase. While these are wildly divergent opinions, the true value of the ODA likely resides somewhere in between.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.020 | 0.010 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".