Building leaders for the UN Ocean Science Decade: a guide to supporting early career women researchers within academic marine research institutions
Bibliographic record
Abstract
Abstract Diverse and inclusive marine research is paramount to addressing ocean sustainability challenges in the 21st century, as envisioned by the UN Decade of Ocean Science for Sustainable Development. Despite increasing efforts to diversify ocean science, women continue to face barriers at various stages of their career, which inhibits their progression to leadership within academic institutions. In this perspective, we draw on the collective experiences of thirty-four global women leaders, bolstered by a narrative review, to identify practical strategies and actions that will help empower early career women researchers to become the leaders of tomorrow. We propose five strategies: (i) create a more inclusive culture, (ii) ensure early and equitable career development opportunities for women ECRs, (iii) ensure equitable access to funding for women ECRs, (iv) offer mentoring opportunities and, (v) create flexible, family-friendly environments. Transformational, meaningful, and lasting change will only be achieved through commitment and collaborative action across various scales and by multiple stakeholders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".