The ‘8Gs’—a blueprint for Geoheritage, Geoconservation, Geo-education and Geotourism
Bibliographic record
Abstract
In the growing field of Geoheritage, Geoconservation, Geo-education and Geotourism, there is a need to manage sites of geoheritage significance. While there is some great geology in nature available to appreciate for scenic value, education, tourism and research, many locations need to be protected from people and commercialism (e.g. the Iridium layer at the K/T boundary in Gubbio, Italy, the Ediacaran fauna in South Australia, the Burgess Shale in Canada or the zircon crystals at Jack Hills, among many others), and some locations need hazard management to protect people (e.g. continuously collapsing cliffs that have potential to be hazardous via rock falls, or slippery slopes, or high cliffs that are treacherous, or ‘king waves’ on rocky shores). The concept of the ‘8Gs’ is intended as a policy-style guidance that logically and progressively links Geology and Geoheritage through a series of steps to Geo-education and Geotourism. There is a logical progression from Geology the Science, through to Geoheritage and the identification of sites of geoheritage significance, to the establishment of Geosites/Geoparks, Geoconservation, leading to Geomanagement, Geo-education and Geotourism. Geomanagement needs to be undertaken prior to the use of sites for Geo-education and Geotourism. In relation to Geomanagement, sites need to be investigated for safety issues, and for the protection of their geological features. Geodiversity, the eighth ‘G’, is outside the progression but plays an important part in underpinning biodiversity. There is also a need to address and manage geodiversity in a given region or specific site to help understand and manage biodiversity.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.015 | 0.020 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".