The 2022 ADEA Climate Study in US and Canadian Dental Schools and Allied Dental Programs—Preliminary Research
Notice bibliographique
Résumé
OBJECTIVES: Dental and allied dental educators train future providers that will work in increasingly more diverse environments in which the non-Hispanic White population in the United States will become a minority (47%) by 2050. The objective was to determine the feasibility and need of conducting an ADEA-led climate study of dental schools and allied dental programs in the United States and Canada. Specifically, Aim 1 was to assess the perceptions of deans and program directors of previous climate assessments in their institutions. Aim 2 focused on assessing these academic leaders' considerations concerning a future ADEA-led climate study. Aim 3 was to explore dental and allied dental diversity officers' considerations of the influence of COVID-19 and the Black Lives Matter movement on such a project. METHODS: In 2020, data were collected with two surveys from dental deans, two surveys from allied dental program directors, and two surveys from diversity officers in the United States and Canada. Two focus group studies were also conducted. RESULTS: The perceptions of dental deans and allied dental program directors of previous climate-related research in their institutions differed widely, with a majority agreeing that they would be likely/very likely to participate in an ADEA-led climate study. Concerning such a future climate study, both groups of respondents agreed/agreed strongly that a climate study should collect data from specific groups of dental school and allied dental program members with different social identity characteristics. They also agreed that ADEA should collect information about community members' well-being and stress, sense of belonging, perceptions of discrimination and harassment, and experiences with discrimination and harassment. Findings concerning the effects of COVID-19 on their institutions' climate were mixed. While allied dental program respondents did not consider COVID-19 had a considerable effect, dental school participants perceived a moderate-to-major effect of COVID-19 on their climate. Focus group participants pointed out that resources were scarcer due to COVID-19. CONCLUSIONS: Overall, preliminary literature review results and survey and focus group findings supported and informed plans to conduct an ADEA-led joint dental school and allied dental program climate study in the United States and Canada.
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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 | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».