Inspiring the chefs of tomorrow with Ashley Marsh [Podcast]
Notice bibliographique
Résumé
In this episode, James Golding speaks with chef lecturer and food-education advocate Ashley Marsh, a member of the Royal Academy of Culinary Arts, educator at the University of West London, and lead for the Chefs Adopt a School programme. His career spans professional kitchens, international events and extensive community outreach, all driven by a commitment to building young people's confidence and curiosity through food. Ashley shares how his passion began with family influences especially his grandmother and uncle and how cooking helped him gain confidence as a teenager. Early career experiences in Australia taught him discipline and the value of strong mentors. After time in business and industry catering, he moved into education, combining practical expertise with a mission to support the next generation of chefs. At the University of West London, Ashley focuses on practical skills, leadership, sustainability and seasonality. He and James discuss the importance of collaboration between hospitality and education to attract and retain new talent. Ashley outlines the Chefs Adopt a School programme, which teaches taste and sensory exploration, knife skills and cooking to help children understand food origins, build confidence, and try new ingredients. With many families lacking time or confidence to cook at home, school engagement becomes crucial and the results are immediate: children grow more curious and willing to taste new foods. The conversation highlights challenges young people face, from social media pressure to increasing anxiety around food. Ashley believes food education provides grounding, community and resilience. He shares memorable stories from working with young people and about his annual Christmas volunteering with Ronald McDonald House, where cooking for families reinforces the emotional impact of hospitality. James and Ashley compare international food cultures, reflecting on Italian festivals where teenagers confidently prepare traditional dishes. These experiences reinforce Ashley's belief that the UK needs stronger food engagement across homes, schools and communities. Ashley also uses pure maple syrup in teaching to discuss seasonality, provenance, natural sweetness and healthier alternatives to refined sugar showing how any ingredient can spark learning. The episode closes with a call for deeper partnerships between chefs, schools and the hospitality sector, and a more positive narrative about careers in food. Ashley believes hospitality offers creativity, opportunity and global pathways and that early, inspiring food education helps young people grow in confidence and find their place in the industry. Follow https://www.instagram.com/alice.fevronia/ and Maple from Canada UK www.instagram.com/maplecanadauk/ for more seasonal recipe inspiration.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,011 | 0,002 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,006 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,085 | 0,026 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».