Genomics research: world survey of public funding.
Bibliographic record
Abstract
BACKGROUND: Over the past two decades, genomics has evolved as a scientific research discipline. Genomics research was fueled initially by government and nonprofit funding sources, later augmented by private research and development (R&D) funding. Citizens and taxpayers of many countries have funded much of the research, and have expectations about access to the resulting information and knowledge. While access to knowledge gained from all publicly funded research is desired, access is especially important for fields that have broad social impact and stimulate public dialogue. Genomics is one such field, where public concerns are raised for reasons such as health care and insurance implications, as well as personal and ancestral identification. Thus, genomics has grown rapidly as a field, and attracts considerable interest. RESULTS: One way to study the growth of a field of research is to examine its funding. This study focuses on public funding of genomics research, identifying and collecting data from major government and nonprofit organizations around the world, and updating previous estimates of world genomics research funding, including information about geographical origins. We initially identified 89 publicly funded organizations; we requested information about each organization's funding of genomics research. Of these organizations, 48 responded and 34 reported genomics research expenditures (of those that responded but did not supply information, some did not fund such research, others could not quantify it). The figures reported here include all the largest funders and we estimate that we have accounted for most of the genomics research funding from government and nonprofit sources. CONCLUSION: Aggregate spending on genomics research from 34 funding sources averaged around $2.9 billion in 2003-2006. The United States spent more than any other country on genomics research, corresponding to 35% of the overall worldwide public funding (compared to 49% US share of public health research funding for all purposes). When adjusted to genomics funding intensity, however, the United States dropped below Ireland, the United Kingdom, and Canada, as measured both by genomics research expenditure per capita and per Gross Domestic Product.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".