Wheat Research Funding in Australia: The Rise of Public–Private–Producer Partnerships
Bibliographic record
Abstract
summary Wheat Research Funding in Australia: The Rise of Public–Private–Producer Partnerships The Australian wheat research system was transformed profoundly by three institutional innovations. First, in 1990 the Grains Research and Development Corporation (GRDC) was created to provide levy‐funded R&D. Second, in 1994 the Plant Breeder’s Rights Act was passed, providing the legal framework for the collection of end‐point royalties (EPRs), now the primary source of funding for wheat‐breeding activities in Australia. Third, in 1999 the GRDC tendered for the development of three for‐profit public corporations that would invest revenues from EPRs to fund wheat breeding, allowing the GRDC to move upstream to focus on using its levy‐based funding for pre‐breeding research efforts. As of 2012, these breeding firms had each acquired a multinational private partner and had collectively reached the point where EPR revenues were sufficient to cover breeding costs. EPRs provide a very strong form of property rights for breeders such that producers will have to pay higher prices to access improved varieties, with some uncertainty about the extent to which those prices will be free to rise. Together, these three institutional innovations have created a well‐funded and well‐coordinated wheat research system that will enhance Australia’s long‐run competitive position in the global grain market, but with an increasing burden of the costs of innovation borne by the industry.
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 | 0.019 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".