Local Culture and Community Through a Digital Lens: Viewpoint on Designing and Implementing a Virtual Second Look Event for Residency Applicants
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic altered how residency interviews occur. Despite 2 years of web-based interviews, these are still perceived as inferior to in-person experiences. Showcasing a program and location is critical for recruitment; however, it is difficult to highlight the program's location and community digitally. This article presents the authors' viewpoints on designing and implementing a virtual second look for residency applicants. OBJECTIVE: Our objective was to host a web-based event to feature the benefits of living in Winston-Salem, North Carolina, for residency applicants, enhance recruitment efforts, and ensure a successful residency match. The goal was to cover topics that interested all applicants, highlight how Winston-Salem is a special place to live, involve current residents, and engage community members. METHODS: Three programs-child neurology, neurology, and family medicine were chosen for a pilot virtual second look. All residency program directors' were asked to recommend community contacts and help identify residents and faculty who may serve as content experts on one of the topics in the panel discussions. A total of 24 community leaders from restaurants, venues, schools, and businesses were contacted, and 18 agreed to participate. The panel discussions included living in and raising a family in Winston-Salem, experiencing Winston-Salem arts and music, where to eat and drink like a local, and enjoying sports and outdoors in the area. The 2-hour event was hosted on Zoom. Postevent feedback assessments were automatically sent to each registrant through Research Electronic Data Capture (REDCap). This study was deemed exempt from Wake Forest University Health Sciences institutional review board review (IRB00088703). RESULTS: There were 51 registrants for the event, and 28 of 48 registrants provided postevent feedback, which was positive. The authors found in the MATCH residency results that 2 of 2 child neurology positions, 4 of 6 adult neurology positions, and 1 of 10 family medicine positions attended our second look event. One adult neurology resident who did not participate was an internal candidate. All respondents agreed or strongly agreed that the session was valuable, well organized, and met their expectations or goals. Furthermore, all respondents gained new information during this web-based event not obtained during their interview day. CONCLUSIONS: The virtual second look event for residency attendees featured the benefits of living in Winston-Salem, and the perspectives of current residents. Feedback from the session was overall positive; however, a top desire would be devoting more time for the applicants to ask questions directly to the community leaders and our resident trainees. This program could be reproducible by other institutions. It could be broadened to a graduate medical education-wide virtual second look event where all medical and surgical programs could opt to participate, facilitating an equitable opportunity for prospective applicants.
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 | 0,011 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,013 | 0,011 |
| Communication savante | 0,008 | 0,004 |
| Science ouverte | 0,002 | 0,012 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
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 ».