Agricultural Learning For the Association of Community Colleges of Canada EXECUTIVE SUMMARY
Bibliographic record
Abstract
Research Council) were directed by a project steering committee representing ACCC and seven Canadian colleges delivering programs to agricultural learners. The team adapted a methodology developed by Grier and his colleagues in Denmark and India for the World Association of Industrial Technological Research Organizations that identified best practices for managing research organizations to one that addressed the needs of this project. Based on findings of a literature search and input from the steering committee, the team created a conceptual model that used the business school marketing model to define the processes important to learning in colleges delivering learning programs in agriculture. A survey tool was developed from the model and was used to collect information from nine Canadian and six international institutions delivering college level agricultural programs on practices that these institutions considered innovative or especially effective. Key findings were: • Colleges have implemented many new practices for promoting to potential
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.096 | 0.020 |
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".