GeoLatinas Mentoring Team: Breaking Barriers & Building Futures through Mentoring Initiatives in the Latinx Community
Notice bibliographique
Résumé
GeoLatinas, a not-for-profit, international organization founded in 2019, promotes and supports Latina women in Earth and Planetary Sciences. Our organization has team-led initiatives focused on mentoring, education, and outreach for professional and personal development. It promotes sustainable training, and peers inspire individuals towards career advancement. GeoLatinas volunteers lead these efforts within the Leadership Council and Local Teams through co-leadership and peer mentoring practices, offering all members the opportunity to join existing or create new initiatives. Launched in 2020, the GeoLatinas Mentoring Team started with a one-to-one mentoring strategy. During this period, the team facilitated 50 mentor-mentee pairs matched according to the mentees’ aims and mentors’ intentions. Through this program, we retrieved insightful information that led us to understand our community’s needs and tailor our approach accordingly. Our priority was to build a safe space that supports our members and addresses the existing Latinx mentoring experiences, challenges, and opportunities literature gap. Hence, “GeoLatinas mentoring program: the process of creating a safe space to grow professionally by co-leadership” enclosed the results and lessons learned from this mentoring experience. This book’s chapter provides relevant and updated information on the status quo of Latinx in the geoscience field (Navarro–Pérez et al., 2025). More recently, between 2024 and 2025, we joined the Mentoring365 platform sponsored by AGU. Within this platform, we designed four different mentoring circles in Spanish, each lasting between two and six weeks. These sharing spaces boosted our community’s knowledge about mentoring, scientific writing and presentations, and the use of the platform itself. The platform closed permanently this year. Thus, our next steps include creating similar virtual places to discuss outstanding key topics related to authorship rights, life in academia as an immigrant, and mentoring at different career stages. This will benefit from the use of other free-sourced platforms (e.g., Slack) for accessibility of our international community. Thus, GeoLatinas remains committed to supporting and empowering Latinx communities in geosciences in response to recent challenging events. Launched in 2020, the GeoLatinas Mentoring Team started with a one-to-one mentoring strategy. During this period, the team facilitated 50 mentor-mentee pairs matched according to the mentees’ aims and mentors’ intentions. Through this program, we retrieved insightful information that led us to understand our community’s needs and tailor our approach accordingly. Our priority was to build a safe space that supports our members and addresses the existing Latinx mentoring experiences, challenges, and opportunities literature gap. Hence, “GeoLatinas mentoring program: the process of creating a safe space to grow professionally by co-leadership” enclosed the results and lessons learned from this mentoring experience. This book’s chapter provides relevant and updated information on the status quo of Latinx in the geoscience field (Navarro–Pérez et al., 2025). More recently, between 2024 and 2025, we joined the Mentoring365 platform sponsored by AGU. Within this platform, we designed four different mentoring circles in Spanish, each lasting between two and six weeks. These sharing spaces boosted our community’s knowledge about mentoring, scientific writing and presentations, and the use of the platform itself. The platform closed permanently this year. Thus, our next steps include creating similar virtual places to discuss outstanding key topics related to authorship rights, life in academia as an immigrant, and mentoring at different career stages. This will benefit from the use of other free-sourced platforms (e.g., Slack) for accessibility of our international community. Thus, GeoLatinas remains committed to supporting and empowering Latinx communities in geosciences in response to recent challenging events.
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 | 0,009 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».