Mindfulness and meditation - Training our spidey-senses for critical qualitative health research
Notice bibliographique
Résumé
I’ve been training students in mindfulness and meditation for over 10 years. What began as a pedagogical survival tool (for my own mental health) soon emerged as something that was incredibly beneficial to my public health students. Turns out sitting in silence, anchoring ourselves in the present moment, and not doing but instead being, is not only good for your physical, social, and emotional health, it’s a great tool for learning. Students report that closing their eyes and sitting together in meditation fosters trust and compassion and builds a sense of community. These feelings allow them to take risks in their learning, to deeply engage with the material, and to participate openly and creatively in ways that foster real growth. During the pandemic I’ve had time to reflect on what I have observed is another benefit of mindfulness and meditation training – that these practices help students develop important skills – or spidey-senses – that are the superpowers of critical qualitative health researchers. These include the ability to be fully present in our work, to listen deeply, to be curious and non-judgemental, to not be attached to outcomes and what we expect to hear or learn, to come to each study and each participant with ‘beginners mind’, to prioritize different ways of knowing, and to accept when things don’t go according to plan (as they always seem to do in qualitative research). In this presentation I welcome all superhero’s and in particular those interested in developing their own and their students spidey-senses. In our time together I’ll share some of the science on why this practice makes good scientists, demonstrate a practice, and provide some tips for those interested in trying it in their own classrooms. During the pandemic I’ve had time to reflect on what I have observed is another benefit of mindfulness and meditation training – that these practices help students develop really important skills – or spidey-senses – that are the superpowers of critical qualitative health researchers. These include the ability to be fully present in our work, to listen deeply, to be curious and non-judgemental, to not be attached to outcomes and what we expect to hear or learn, to come to each study and each participant with ‘beginners mind’, to prioritize different ways of knowing, and to accept when things don’t go according to plan (as they always seem to do in qualitative research). In this presentation I welcome all superhero’s and in particular those interested in developing their own and their students spidey senses. In our time together I’ll share some of the science on why this practice makes good scientists, demonstrate a practice, and provide some tips for those interested in trying it in their own classrooms.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,018 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».