GeoLatinas’ vision: Nurturing, promoting and fostering leadership, teamwork and collaboration to sustain synergies between academia and industry
Bibliographic record
Abstract
Substantial differences in academia and industry’s working culture create challenges in establishing collaborations and raise obstacles for professionals transitioning across sectors. For minoritised groups and young generations in Latin America, the absence of role models in leadership positions, language barriers, lack of staff retention, gender discrimination and non-inclusive working spaces result in an even more challenging environment. In light of current and historical social challenges that our demographics and other marginalised groups face, GeoLatinas’ visionary purpose offers a platform to empower Latinas in Earth and Planetary sciences. Our community intends to create an inclusive, safe space for students, scientists and professionals from different backgrounds to converge. Since its foundation in 2018, GeoLatinas has established synergies between academia and industry by actively encouraging participation with other organisations and professional associations, and among its members. The intentional balance between academia and industry’s perspectives —as reflected in our circular organisational structure— has allowed GeoLatinas to effectively embrace professionals at different career stages. As a result, we have built a community to share experiences, personal successes, challenges, and coping mechanisms. We aim to mitigate barriers that prevent the successful transition between sectors by developing and implementing initiatives. In this way, we strengthen connections in our network and our community, focusing on key best practices and innovative actions for change. At GeoLatinas, we focus on nurturing, promoting and fostering leadership, teamwork, and collaboration in our members to thrive in academia and industry. Our organisation provides visibility and access to role models around the world. They represent a wide spectrum of knowledge, experience and background, offering students and professionals a platform to strengthen their skills in a safe environment. During a nurturing phase, GeoLatinas stimulates members’ accountability and individual efforts through the creation and proactive management of local teams and initiatives. Their implementation leads to the promoting phase, where we motivate representation and leadership by recognising and broadcasting our community’s accomplishments worldwide in the GeoLatinas Newsletter and social media channels. Initiatives focused on career development, like our Mentoring programme and the PERLA (Professional exchange for Resilience, Leadership and Advancement) initiative, facilitate direct communication of professionals working in academia and industry with our members. These actions create exposure and awareness of real-world barriers faced in both sectors, providing strategies to address them. As a result, our leaders thrive in project management, delegation, negotiation or collaborative teaching, applicable in every professional environment. Other initiatives, like our Scholarship & Jobs database gather data that our members use to find academic and industry positions, while our Dry Runs & Peer Review subcommittee provides members with feedback on, for example, their application process. Finally, in a fostering phase, a collaborative culture allows us to put our gained skills and outputs from the GeoLatinas’ initiatives at the service of the broader scientific community, leading to the emergence of new role models. GeoLatinas intentional efforts have proven that nurturing, promoting and fostering members in impactful platforms can lead to career advances to stimulate collaborations and support career transitions within our community, bringing academia and industry closer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".