Exchanging knowledge in community online seminars: lessons learned from the Rifts and Rifted Margins Seminar series
Bibliographic record
Abstract
The Rifts and Rifted Margins Seminar is a community-based, international online seminar series. It unites multi-disciplinary expertise in the fields of geology, geophysics, and geochemistry, and aims at covering both fundamental and applied research aspects. The series caters primarily to the community working on active rifts and the one that focusses on rifted margins. We aim to bridge these communities while further, building links to neighboring disciplines.The seminar series started in June 2020 and has hosted about 70 seminars with roughly 200 individual talks1. Each seminar session is structured as a one-hour Zoom meeting held on Monday afternoon European time. Originally a bi-weekly meeting, the seminar has switched to a monthly rhythm since summer 2022. If speakers agree, their presentations are recorded and shared on the seminar’s YouTube channel2.We have encountered several challenges since the inception of this project – from technical hurdles to defining the scientific scope of the seminars. We have adopted a technical setup that utilises Zoom for video conferencing, accommodating over 100 attendees at times, DFN3 for broadcasting invitations to a mailing list of more than 700 subscribers, and YouTube for hosting seminar recordings that have gained approximately 40,000 views2. In contrast to the majority of other online seminars, we host three speakers per session, each at different career levels (senior, mid-level, and early career/student) and where possible, from different gender/ethnic groups, delivering a talk of 13-15 minutes length. These presentations concentrate on a single scientific subject, albeit from varied viewpoints. We believe that this setup ensures a more diverse perspective and enhances the discourse. On the downside, it complicates the scheduling of sessions.In total, 10 researchers have contributed to organizing this seminar series since 2020. To meet individual time commitments and to ensure influx of new ideas, the initial team of organizers has been steadily replaced. The pandemic has seen the emergence of many online seminars which have played a key role in maintaining community connections during that time. The principal advantage of online seminars however endures beyond the pandemic: they enable the exchange of knowledge without the need for travel and with a minimal carbon footprint, accessible to anybody with an internet connection, and at no cost. [1] https://www.gfz-potsdam.de/sektion/geodynamische-modellierung/projekte/rift-and-rifted-margins-online-seminar[2] https://www.youtube.com/@riftandriftedmarginsonline1714/playlists[3] https://www.dfn.de/
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".