Summer schools of the HOSST-TOSST graduate programme: a multi-sector approach towards scientific communication and outreach
Bibliographic record
Abstract
The goal of the HOSST-TOSST programme is to cultivate the next generation of advocates of the ocean. As we enter a time where all kinds of opinions are formed through the rapid exchange of unfounded information, the importance of science stays ever crucial as it could and should serve as a common ground based on factual evidence and analytical reasoning. The programme directly embedded training for scientific communication and outreach methods at the very beginning of the careers of the next generation of ocean scientists. One of the ways was through various mandatory summer schools located in marine institutes across the North Atlantic. The summer schools challenged our doctoral candidates from diverse disciplines to collaborate in teams. Each team was assigned with a mini-project, where communication and outreach were essential for their success. In Halifax, Canada, the project aim was to create business proposals or products that would be financially viable whilst not encumbering the already struggling ocean. In Kiel, Germany, the end goal was to come up with proposals for Marine Protected Areas in the busiest regions of the Atlantic, all the while navigating between various stakeholders and other ocean users to come up with the best compromise. In Mindelo, Cabo Verde, the participants, including local students, did field research and presented findings on geological processes and marine ecosystems which directly influence the lives of the residents. The summer schools aimed to instill an awareness of how to conduct scientific communication and outreach to the general public from a multi-spectrum approach. The variety within the three projects, places and the diverse communities involved have all contributed to discussions leading to a broader view on the issues, possible solutions and scientific questions that remain open surrounding the Atlantic Ocean in all its facets.
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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 | 0.016 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.095 | 0.019 |
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".