The “Finnish Phenomenon” in Geoscience Education
Bibliographic record
Abstract
The declining popularity of geosciences in higher education (HE) globally has increased concern about an emerging skills gap in the geoscience workplace. Australia, Canada, the US, the UK, and Italy have observed a decline in graduates, enrolment, and/or applicant numbers of typically 20 to 40% in graduate/undergraduate geoscience programs since 2013. Geoscience educators tend to attribute these trends to negative public perception of geosciences in relation to environmental and climate change and general lack of awareness about societal relevance of the field.The opposite trend has been observed in Finland over the past eight years. Degree programmes in geology or geosciences in Finland have jointly experienced a total increase of ca. 70% both in applicant numbers (2020–2024) and enrolment (2015–2024). The Finnish geoscience education community coined the term “Finnish phenomenon” to describe these positive observations. However, the reasons behind these observations remain to be understood. As the overall applicant numbers to Finnish universities do not follow these trends, education system level effects can most likely be ruled out.This contribution explores some of the activities and changes in the Finnish geoscience higher education processes during the past ca. 10 years that could explain the “Finnish phenomenon”: 1. Changes in the Finnish HE admission systemIn 2015, the Finnish HE application process (joint application system) was transferred to the digital Studyinfo.fi-portal (https://opintopolku.fi/konfo/en/). Since 2022, all geoscience degree programmes have hosted a joint landing page within the portal to enhance the visibility of the field. 2. International Earth Science Olympiad (IESO) activitiesSince 2018, the visibility of geosciences in Finnish schools has been enhanced through the activities of the International Earth Science Olympiad (IESO). National IESO efforts coordinated through the Geological Society of Finland have increased the visibility of geosciences among students and led to success in the international competitions. 3. Upper secondary school collaboration in geosciencesGeosciences are not taught as a separate subject in Finnish upper secondary schools. Since 2020, secondary school collaboration has been systematically enhanced especially at the University of Helsinki through a working group that includes staff, students, City of Helsinki education services, and schoolteachers. 4. The FIN-GEO networkOne of the major joint efforts in the Finnish geoscience education community in recent years has been the FIN-GEO project funded by the Ministry of Education and Culture of Finland in 2021–2023. The FIN-GEO network significantly strengthened cooperation in the education of geosciences, utilizing the mutual research profiling of the parties in the development of educational offerings and the relevance of working life. The annual geoscience first-year questionnaire launched by the FIN-GEO network in 2022 has found that the Studyinfo.fi-portal alongside geoscience-specific media coverage and university webpages have been the most important sources of information for aspiring students. Further analysis of these results is ongoing, but combined the actions listed above appear to have positively affected interest in higher geoscience education, which could serve as a useful template elsewhere as well.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".