Learning about the forest using alternative curricula the Guelph experience
Bibliographic record
Abstract
The University of Guelph is a mid-sized university in southern Ontario that has many historical underpinnings with respect to both undergraduate and graduate education in forestry and forest-related subjects. Some of the earliest forward-thinking forest policies found in Ontario came from early faculty associated with the predecessor of the University, the Ontario School of Agriculture. Today, the University has numerous faculty in Colleges across campus that are involved in a multitude of teaching and research aspects associated with forested environments. The research-teaching link with respect to forestry is strong and the undergraduate population appears appreciative of this. Undergraduate courses and course segments at both undergraduate and graduate levels exist, and a minor in forest science, housed in the Department of Environmental Biology but drawing on resources from across multiple disciplines, is also available. The University of Guelph is currently evaluating its options with respect to undergraduate education in the forest sciences. Building on past and present strengths, the University is considering offering a non-accredited B.Sc. program that embraces the science and management of forests and the environmental impact and community benefits associated with interventions in the forest. Key words: Ontario forests, historical perspectives, learner-centred undergraduate curriculum, forest environments, forest science, forest and natural resource economics, internationalism, non-accredited B.Sc. undergraduate degree, graduate forest research
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".