Geosciences are Important for Humanity! A Model for Enhancing the Geoscience Narrative across Canada
Bibliographic record
Abstract
“Geosciences are important for humanity” is the central message of a model presented to promote the geosciences as essential to the development of Canada and the world. Components of the geosciences directly or indirectly address all 17 UN Sustainable Development Goals, and geoscientific knowledge is essential in efforts to address climate change. Despite this broad relevance, many Canadians remain unaware of the importance of the geosciences, partly because the discipline is not consistently offered as a standalone high school course in all provinces and territories. The number of students entering undergraduate geology major programs declined by over 40% between 2015 and 2022, and this creates challenges within Canada’s workforce. Currently, gaps in the workforce are filled through immigration, but the federal government is now starting to limit immigration. The seven components of the proposed model include: public engagement to promote the geosciences in varied settings; engagement with politicians and policy makers; engagement with resource and other industries; development and implementation of strategic plans to promote improved awareness of the geosciences; development of public education, outreach and communication programs; promotion of courses and engagement programs at post-secondary institutions; and coordination with geoscience societies and geological surveys. Hosting the International Geological Congress (IGC) 2028 could unite the Canadian geoscience community by strengthening connections between academic geoscientists and government, advocating for a Canadian Research Chair related to geoscience education and outreach, developing an inventory for geoscience education and outreach programs, and exploring creative ways to develop standalone geoscience courses in high school. If all Canadian geoscientists use the model components to emphasize the importance of the geosciences to humanity, we can collectively work towards better public understanding of the relevance of the geosciences to most aspects of life in Canada and improve the future of our vital discipline.
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 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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.049 | 0.016 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".