Evaluation of Agri‐Environmental Programs: Can We Determine If We Grew Forward in an Environmentally Friendly Way?
Bibliographic record
Abstract
Abstract The environmental elements of the quinquennial agricultural policy frameworks are probably the largest agri‐environmental programs in Canada and have been running for about 15 years. Formal evaluation of their effectiveness has either not been done, or is not available for researchers and policy analysts to compare with other agri‐environmental policy efforts. This address introduces this problem and attempts to examine evaluative approaches using Alberta's Growing Forward 1 and 2 environmental stewardship programs. While this attempt has uncovered significant data issues, there is evidence that program managers targeted funds to areas where water quality risks are of concern. The review also questions the requirement that producers eligible for funding must have an Environmental Farm Plan. After 15 years of having this requirement, I argue that it's time for Alberta's environmental stewardship program to relax this. Les éléments environnementaux des cadres politiques agricoles quinquennaux représentent probablement les plus vastes programmes agroenvironnementaux au Canada et opèrent depuis environ quinze ans. L'évaluation formelle de leur efficacité n'a soit pas été entreprise, ou n'est pas disponible pour les chercheurs et analystes politiques afin qu'ils les comparent à d'autres efforts en matière de politique agroenvironnementale. Cet énoncé présente ce problème et tente d'examiner les approches évaluatives utilisées par les programmes albertains de gérance environnementale Cultivons l'avenir 1 et 2. S'il est vrai que cette tentative a révélé de considérables problèmes de données, des preuves démontrent que les gestionnaires de programmes dirigeaient les fonds vers les régions où la qualité de l'eau est en jeu. L'évaluation s'interroge aussi au sujet de l'exigence selon laquelle les producteurs admissibles au financement doivent présenter un plan agroenvironnemental. Ayant été requise pendant quinze ans, je propose que le programme de gérance environnementale de l'Alberta assouplisse cette exigence.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".