Review: Industry levy-funded pulse crop research in Canada: Evidence from the prairie provinces
Bibliographic record
Abstract
Carew, R., Florkowski, W. J. and Zhang, Y. 2013. Review: Industry levy-funded pulse crop research in Canada: Evidence from the prairie provinces. Can. J. Plant Sci. 93: 1017–1028. Since the 1970s the prairies provinces have become a major producer of pulse crops, attributed to diversified cropping systems and the adoption of improved cultivars. This article reviews pulse production trends and research funding for pulse crop research, emphasizing both the contribution of governments and public research institutions/industry arrangements in shaping the growth of the pulse sector. The expansion of pulse production has not been associated with rapid increases in publicly funded research. The study found that industry-/producer-funded research as a share of pulse farm cash receipts has been larger in Saskatchewan and Manitoba than in Alberta. Moreover, the unique consortium arrangement of funding pulse research in Alberta by the provincial government has resulted in larger research intensities than for provincial government funding in Saskatchewan or Manitoba. Furthermore, the intellectual property protection of pulse cultivars since the enactment of the Plant Breeders’ Rights Act in 1990 has increased Canadian producers’ access to field pea cultivars developed by foreign seed companies.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.011 | 0.029 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".