Mentoring is more than a mentor
Bibliographic record
Abstract
Recent work has highlighted the substantial positive impact of multi-dimensional mentoring, particularly a mentoring network, in one’s professional development and overall well-being (SAGE Open 2017; doi.org/10.1177/2158244017710288) (Nat Comm 2022; doi.org/10.1038/s41467-022-28667-0). The Women in Soil Ecology (WiSE) network (https://womeninsoilecology.github.io) was born out of a desire to develop mentoring relationships between women from different institutions and career stages – to fill the gaps in traditional faculty–graduate student advising relationships. These gaps included the need for advice and role models in dealing with issues such as harassment and safety in the field and at conferences, work–life balance, navigating family and childcare responsibilities, equal pay and representation, and being a woman in the male-dominated field of soil science (Soil Sci Soc Am J 2019; doi.org/10.2136/sssaj2019.03.0085). Four years and an ongoing pandemic later, our network has grown into much more than we initially envisioned and now connects women with a passion for soil ecology from across the globe. Mentorship is at the core of what WiSE does but has many facets. We leverage a multitude of events, platforms, and programs to strengthen the vibrant community of WiSE. Virtual Meet and Greet events provide space for discussion of work and life challenges, and fuel networking for collaborations. We use skills-based workshops and career panels to teach and learn from one another, sharing in our personal and professional development journeys. WiSE’s social media and website platforms allow us to share job and funding opportunities, amplify each other’s voices through social media takeovers, and connect with women from all over the world. We organize conference sessions to highlight how women are paving the way in our field both in advancing science and in making soil ecology a more just and equitable community. And with our mentorship program, we coordinate mentoring pairs and trios by matching members across career stages, cultural backgrounds, and institutions (academic and non-academic) worldwide. Moving forward, we plan to expand our mentoring program by providing more diversified and mentor–mentee-specific programs including an Indigenous scholarship, journal club, comprehensive exam support group, and learning community (New Dir Teach Learn 2004; doi.org/10.1002/tl.129). Our ultimate goal is for current and future mentors and mentees to develop and cultivate their own mentorship style where both members learn from each other. This bolsters WiSE’s broader mission for members to develop meaningful relationships focused on shared experiences, knowledge transfer, and support outside the workplace. As our network grows, we keep learning how to support one another, harnessing the incredible potential that we hold both individually and collectively. Above and beyond mentoring, we are working to change the face of soil ecology. We are intentionally amplifying the voices of historically excluded groups of women and redefining what it means to be a ground-breaking scientist (pun intended!). We equally value the fundamental contributions women are making to the field of soil science in scientific research and in broader impacts including science education and communication, land management and restoration, Indigenous engagement, community outreach, and best data practices. We know that the critical intersections between research and diversity, equity, and inclusion efforts will pave the way for more diverse perspectives and enhanced representation in our field, while advancing the next generation of scientific thought. At times, our efforts have been met with resistance. We’ve even been told that “we got it wrong” by incorrectly defining leaders who didn’t fit in the established model. We see these challenges as a sign of the impact we’re having in shifting the status quo and making space for new definitions of success. It also reminds us that despite the substantial progress and opportunity for women in our field, there’s still more work to do. In closing, we want all women, both in our network and beyond, to ask for more: more money, more time off, more meaningful and healthy relationships with their work, and more space to be human when perfection often seems the standard. This requires more than just a mentor, but rather a network of people committed to ensuring we all get more of what we need. This fall, we are hosting an event on negotiating salaries and benefits for early career women. So many of our members have been asking for this training because we have not been taught how to ask for more. Our hope is that WiSE members will continue to learn from our shared experiences, break the mold of what’s expected, and further reshape the field of soil ecology into the equitable community of which we all want to be a part.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".