What’s on the menu? Succulent sustainability goes to school
Bibliographic record
Abstract
Schools are a fertile setting for succulent sustainability. Students can improve their plant-based food literacy and sustainability education while acquiring life and vocational skills. Although the term succulent sustainability is not used in Canada yet, many schools in all regions offer related programmes. This chapter identifies potential components of succulent sustainability; summarizes the status of programmes, policies, and curricula in Canada; and highlights examples of research and programmes. Canadian schools have increased their involvement in plant-based initiatives in a relatively short time. Research and programme examples indicate considerable progress in establishing school gardens, youth leadership programmes, and food sustainability education. Researchers note, however, that more work is needed to reach all students, to offer programmes that address all aspects of food literacy, and achieve systems change. Benefits to students are far-reaching and include increased awareness of food and willingness to try new foods, increased gardening and food preparation knowledge and skills, enhanced social skills, increased school pride, and improved social inclusion within schools. The chapter ends by emphasizing the need for partnerships, strategic planning, educational resources, funding and training, monitoring, and policies to close existing gaps. In sum, Canada requires action at all levels to enable all students and schools to reap the full benefits of succulent sustainability.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".