Food Futures in Education and Society
Bibliographic record
Abstract
"This book brings together a unique collection of chapters to facilitate a broad discussion on food education that will stimulate readers to think about key policies, recent research, curriculum positions and how to engage with key stakeholders about the future of food. Food education has gained much attention because the challenges that influence food availability and eating in schools also extend beyond the school gate. Accordingly, this book establishes evidence-based arguments that recognise the many facets of food education, and reveal how learning through a futures' lens and joined-up thinking is critical for shaping intergenerational fairness concerning food futures in education and society. This book is distinctive through its multidisciplinary collection of chapters on food education with a particular focus on the Global North, with case studies from England, Australia, the Republic of Ireland, the United States of America, Canada and Germany. With a focus on three key themes and a rigorous food futures framework, the book is structured into three sections: (i) food education, pedagogy and curriculum (ii) knowledge and skill diversity associated with food and health learning (iii) food education inclusivity, culture and agency. Overall, this volume extends and challenges current research and theory in the area of food education and food pedagogy and offers insight and tangible benefits for the future development of food education policies and curricula. This book will be of great interest to students, scholars, policymakers and education leaders working on food education and pedagogy, food policy, health and diet and the sociology of food"--
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".