The FAMOS school day: Fostering confidence in a diverse body of early-career polar marine scientists
Bibliographic record
Abstract
The Forum for Arctic Modeling and Observational Synthesis (FAMOS) is a project funded by the U.S. National Science Foundation to advance the science of Arctic physical, chemical, and biological marine modeling. It is further designed to foster collaboration with marine observationalists and those who wish to work with Arctic marine modelers, e.g., atmospheric scientists, glaciologists, hydrologists, terrestrial ecologists. FAMOS holds an annual workshop of ~120 people and spawns numerous collaborative projects that have filled three special JGR collections and more. Attendance at FAMOS workshops is a mix of senior researchers and early-career scientists. The final three days of the 4-day workshop consist of AGU-style short talks, break-out sessions, and panel discussions. But the first day is devoted to the FAMOS School, wherein ~ 40 graduate students, postdocs, and early career polar scientists attend 5 longer-format (~ 35 minute) lectures. Discussion sessions are especially highlighted, and senior scientists in attendance are not allowed to speak. A “wild card” after-lunch session is devoted to various topics, e.g., outreach, alternate career choices, and geoengineering. The day ends with a working dinner in which further discussions and networking occur. School attendees are typically gender-balanced and have included students from non-traditional Arctic countries (e.g., Iran, Brazil, Egypt). The FAMOS School has been very successful, as measured by participant feedback and by the number of applications received (i.e., more than we can accommodate each year). A key outcome has been to bolster confidence in the early-career students, so that they are more willing to actively participate in the following days’ activities. This is also enhanced by naming them as session and discussion chairs, and by suppressing the tendency of senior scientists to “hog the microphone.” Discussion at FAMOS workshops has significantly influenced the focus of many PhD projects and spawned a number of student-led research papers. A main lesson learned from the FAMOS School is that just inviting students to a workshop or into a research community is not enough: One must also take active steps to foster confidence and give them a voice. The good news is that this really works.
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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 | 0.027 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.025 | 0.009 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.004 | 0.049 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.051 | 0.023 |
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".