The ‘8Gs’—a blueprint for Geoheritage, Geoconservation, Geo-education and Geotourism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it