Transprofessional competencies across clinical, organisational, and educational professions: the case of mindfulness-based teaching and learning (MBTL)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study explores mindfulness-based teaching and learning (MBTL) as an emerging field of transprofessional practice spanning educational, organisational, and clinical professions. Recognising the need for a more robust set of transprofessional MBTL teacher competencies to serve this emerging specialisation, the authors developed and validated the Mindfulness-Based Teaching and Learning – Teacher Competency Framework (MBTL-TCF). Building on the pre-existing Mindfulness-Based Interventions-Teaching Assessment Criteria (MBI-TAC), the researchers developed a teaching framework for mindfulness specialists to reflect teacher agency, autonomy, and self-determination consistent with the purposes, traditions, and effects of what MBTL teaches: that is, mindfulness. The paper presents the sequence of construct, face, and content validation procedures, including the alignment of the MBTL-TLC with Dreyfus and other teacher competency frameworks from a range of sectors and countries. Finally, using an adapted Delphi process, a six-member international expert panel plus one diversity reviewer were invited to review and refine the emerging framework. The resulting MBTL-TCF presents 12 competency domains with associated activities and performance indicators.
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.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it