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Enregistrement W4388325995 · doi:10.1016/j.esmoop.2023.102058

On finding acceptance

2023· letter· en· W4388325995 sur OpenAlexaff
David Chen

Notice bibliographique

RevueESMO Open · 2023
Typeletter
Langueen
DomaineMedicine
ThématiqueHealth and Medical Research Impacts
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésFeelingMentorshipPsychologyMedical educationWorkforceMedicineSocial psychologyPolitical scienceLaw

Résumé

récupéré en direct d'OpenAlex

‘Accepted’. This single word drowned out the vernacular in the rest of my acceptance letter to my dream MD/PhD program. In that moment, I was on cloud nine. After all, it was the culmination of both my research and clinical interests that will assuredly set my plan to train as a physician-scientist in oncology into motion. However, celebration soon transformed into empty emotion, and then into anxiety. Why did I feel so lost? To answer this question, my own reflections arrived at many of the same conclusions proposed by Lim et al. that contribute to attrition in the physician-scientist workforce.1Lim K.H. Westphalen C.B. Berghoff A.S. et al.Young oncologists’ perspective on the role and future of the clinician-scientist in oncology.ESMO Open. 2023; 8101625Abstract Full Text Full Text PDF Scopus (3) Google Scholar Beyond the personal, professional, institutional, and national/international factors indicated in this study, I wanted to highlight the often-overlooked but necessary role of mentorship to support the lifelong challenges of the physician-scientist pathway. My pursuit of the physician-scientist pathway was modeled after my own mentors who had completed training in MD/PhD programs. Each convinced me that I had what it takes to train as their future colleague during our intimate career discussions, and I fondly recall feelings of validation that came with my great respect for physician-scientists. I wanted to pursue MD/PhD training to one day fill their shoes. One week before the deadline to confirm my MD/PhD acceptance, I finally pieced together why I felt lost. The dream of MD/PhD training was not my own, but one ingrained by the well-intentioned recommendations of my mentors. When I considered bringing up my personal and practical considerations of this training pathway to my mentors, I expected a mix of shock, heartbreak, and even disrespect. It was none of the above. My mentors were unconditionally faithful and supportive so that I could positively make the right decision for myself. Given inadequate financial funding and my unclear prospects of securing a future position that combines research and clinical duties in the competitive research climate, I could not commit to the pursuit of the MD/PhD with full confidence. After deciding to discontinue my MD/PhD training, I found solace in knowing that my mentors successfully instilled in me the crux of the physician-scientist, regardless of my matriculation into an MD/PhD program—independent, critical thinking. Today, I remain interested in pursuing the physician-scientist training pathway, and find comfort and familiarity in doing so outside of a traditional MD/PhD program with the unconditional support of my research mentors for career and personal advice. As a mentee, we are often enclosed within a microcosm of mentors and find ourselves modeling after their every word due to our dependence for their career advice and letters of recommendation. Encouraging self-discovery by taking the path less travelled requires an unconditional level of faith that only strong mentor–mentee relationships embody. In parallel with our gratitude for our mentors’ support, mentees also owe it to ourselves to make personal decisions based on what feels right for us without fear of retribution for taking paths less travelled. As mentees, we all want to feel accepted in making our own unique decisions, and as future mentors, we should embrace when our mentees expect the same. The author thanks his mentors for their continued guidance and support. None declared.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,032
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,057
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,032
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,004
Charge utile insuffisante (le modèle a refusé de juger)0,0040,008

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.

Tête enseignante Opus0,392
Tête enseignante GPT0,529
Écart entre enseignants0,137 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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