Notice bibliographique
Résumé
I am honored to have been asked to contribute to the APS Mentoring Forum, especially at such an early point of my own career. In terms of my own training journey, I trained at the University of Calgary, Faculty of Medicine, which is a research-focused institution. Here, faculty face high exceptions to land external grants to fund their research and focus on research with advanced trainees (masters, doctoral, and postdoctoral), and are evaluated almost exclusively on research productivity. The teaching they do amounts to a few lectures or course coordination in graduate level classes in their area of expertise. It was an incredible place to train in neurobiology. However, most trainees, when they get out, do not end up with jobs at institutions like this. Following completion of my PhD, I landed a tenure-track instructor position at an undergraduate teaching college, where students completed the first 2 years of their programs and transferred to bigger institutions. At the time, I had heard there were efforts to transform the institution into a bachelor degree granting institution, and I wanted to be a part of the process. We completed this transition in 2010, in both name and membership in the Association of Universities and Colleges of Canada. We rolled out many new degree programs, and I was and continue to be involved in both new curriculum and course development. The transition of Mount Royal College to Mount Royal University in 2010 has come with a lot of changes and growing pains, not the least of which were around academic rank and work pattern transitions to include scholarship. My focus in this article will be around workload and scholarship support in a new university setting that focuses its efforts on teaching and training undergraduates. My comments are aimed at relatively new faculty who are trying to start a research program with the inclusion of undergraduate students at a teaching-focused undergraduate institution. Additionally, instructors at small liberal arts colleges may find my experience helpful if they want to get started, either at their own institutions or in collaboration with other universities. If you are a Chair or a Dean interested in supporting the development of research programs, my experiences outlined below may help in framing the justification for and in securing resources to support these activities. Post-PhD, not everyone is going to get jobs in researchintensive institutions. If you are one of those new to mid-career faculty members at a small teaching-focused undergraduate institution trying to get started with a research program, this column is aimed at you.
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 | 0,024 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,006 |
| Communication savante | 0,013 | 0,005 |
| Science ouverte | 0,001 | 0,014 |
| Intégrité de la recherche | 0,002 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,040 | 0,026 |
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 ».