Inspiring a plant-based transformation within the foodservice industry
Bibliographic record
Abstract
Humane Society International (HSI) works with foodservice professionals and foodservice operations to add more plant-based options to their menus. This chapter details HSI’s work to improve the food system around the globe, with a focus on its innovative Forward Food culinary resource program in Canada. HSI/Canada’s Forward Food program supports foodservice management companies, large-scale institutions, restaurants, food distributors, culinary professionals, and others in putting plants at the centre of the plate. Forward Food offers culinary training, recipe, and menu development support, guidance on marketing and communications, educational sessions, and greenhouse gas impact assessments to help the foodservice industry meet the increasing demand for delicious, accessible, plant-based options. HSI’s pragmatic approach to food system change has achieved meaningful results, based on coaching the foodservice industry on the why and how of sustainable eating interventions for lasting success.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".