Geoscience Education Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science
Bibliographic record
Abstract
Abstract Practitioners and researchers in geoscience education embrace collaboration applying ICON (Integrated, Coordinated, Open science, and Networked) principles and approaches which have been used to create and share large collections of educational resources, to move forward collective priorities, and to foster peer‐learning among educators. These strategies can also support the advancement of coproduction between geoscientists and diverse communities. For this reason, many authors from the geoscience education community have co‐created three commentaries on the use and future of ICON in geoscience education. We envision that sharing our expertise with ICON practice will be useful to other geoscience communities seeking to strengthen collaboration. Geoscience education brings substantial expertise in social science research and its application to building individual and collective capacity to address earth sustainability and equity issues at local to global scales The geoscience education community has expanded its own ICON capacity through access to and use of shared resources and research findings, enhancing data sharing and publication, and leadership development. We prioritize continued use of ICON principles to develop effective and inclusive communities that increase equity in geoscience education and beyond, support leadership and full participation of systemically non‐dominant groups and enable global discussions and collaborations.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".