The 2022 ADEA Climate Study in US and Canadian Dental Schools and Allied Dental Programs: Methodological Considerations
Notice bibliographique
Résumé
OBJECTIVES: From January 2020 to the end of August 2020, preliminary research gathered data about the need for and the feasibility of an ADEA-led joint Climate Study of dental schools and allied dental programs in the United States and Canada. Informed by these findings, the first ever ADEA-led joint Climate Study took place in 2022. The objectives of this manuscript were to describe the timeline of this climate study and provide information about its methodology, specifically about (a) who participated in this research, (b) what was assessed, (c) how the study was conducted, and (d) how the results were communicated. METHODS: In 2021, the consulting company Nonprofit HR, members of the ADEA Collaborative on Dental Education Climate Assessment and campus liaisons collaborated on designing the 2022 ADEA-led Climate Study. RESULTS: Between January 1 and March 31, 2022, survey data were collected in the United States (N = 16,518), Canada (N = 1042), and Puerto Rico (N = 145) from 10,281 students, 2591 staff, 4026 faculty, 359 administrators, and 443 administrators with faculty positions in dental schools and allied dental programs. Social identity information about the respondents' gender identity, ethnicity/race, sexual orientation, and ability status was assessed. Survey questions focused on assessing respondents' perceptions/experiences with their own institutions' climate and the degree to which it was inclusive. The questionnaire collected information about their well-being, sense of belonging and cultural competence, their perceptions/experiences with harassment and discrimination, with their institutions' diversity, equity, and inclusion-related programming, activities, and leadership practices. Careful attention was given to how the data were collected and how the results were shared with the participating academic institutions and the dental education community at large. CONCLUSIONS: Institution-specific results of this 2022 ADEA Climate Study were shared with the participating dental schools and allied dental programs to provide them with a better understanding of their own cultural climate. This special issue of the Journal of Dental Education provides dental educators with an overview of the results of this first ever ADEA-led Climate Study of U.S. and Canadian dental schools and allied dental programs.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».