P165: A Non-hierarchical mentorship model for professional development
Notice bibliographique
Résumé
Introduction: Mentorship is an essential component of professional development and benefits include increased career satisfaction, scholarship, and efficiency of academic promotion. The Mastermind group, a collaborative, network-based model for mentorship has gained popularity in the business world. It comprises of a group of colleagues that provide mentorship and career advice for each other through regularly scheduled meetings. The group benefits from the combined intelligence and accumulated experience of the participants, who may be at different career stages. Methods: Academic Life in Emergency Medicine (ALiEM; www.aliem.com ), a digital health professions education organization, conducted two Mastermind groups for 14 team members in 2017. The groups included all levels of academic rank from full professor to instructors, and represented 14 different medical schools in North America. Each Mastermind group completed a self-assessment summarizing their professional strengths and weaknesses, two homework assignments, and two 90-minute videoconference meetings, using a structured, moderator-facilitated format. Meetings were conducted on Google Hangouts on Air© (Google Inc.). In the initial group meeting, participants discussed their self-assessments, current projects, and career challenges. The second meeting allowed discussion of suggested professional development resources for each participant, actionable next steps, and an accountability timeline for each participant. The free, cloud-based platforms and voluntary basis for the Mastermind groups resulted in a zero-cost innovation. Results: In a post-intervention survey, the 14 participants rated the experience as 9.4/10 (response rate 100%) using a Likert scale. In a quasi-experimental analysis participants cited the need for career advice or assistance with a project as their reason for participating. Participants received specific resource recommendations during the sessions, including books, training courses, or conferences. Contacts outside the group for additional mentorship were made possible given the breadth of networks among the participants. All participants had at least one identifiable next step with accountability to the group. Overall, the participants described a synergy of energy, commitment to one anothers longitudinal success, and benefit from the diverse range of talent and expertise in the group. Many of the members discussed plans to replicate this mentorship model at their own institutions. Conclusion: Our experiences suggest that the Mastermind conceptual framework is an easily replicated, feasible, zero-cost, and effective model for professional development. Though the model was originally proposed as a method for in-person discussions, we report a more modern, online experience for professional development in our diverse, globally-distributed team.
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 | 0,007 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 0,007 |
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 ».