THE EMERGING FIELD OF GEOETHICS
Bibliographic record
Abstract
The geosciences need practitioners who possess an ethical conscience and the desire to act responsibly. Ethically responsible geoscientists will achieve success and satisfaction by carrying out excellent research and professional activities, and by maintaining honest and open collaborations with colleagues. Such individuals will be able to contribute to building a resilient society, be better prepared to face global economic and environmental challenges and be willing to take concrete actions for the conservation of the geo-environment. Geoethics provides ethical, social, and cultural values for the scientific community and for society as a whole. Geoethics represents a new vision of a world in which it is possible to maintain a more balanced relationship between humans and nature, considering modern economic and social development expectations. This chapter illustrates some aspects of geoethics, provides an overview of its basic values and themes, and highlights prominent global issues that involve geoethics, including climate change, geo-risks, land management, exploitation of geo-resources, and sustainability. The International Association for Promoting Geoethics (IAPG) provides a multidisciplinary platform for discussion, a place where multidisciplinary collaboration can strengthen the development of geoethics from a scientific and philosophical perspective, in order to better introduce geoethical values into society.
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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 | 0.020 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.022 | 0.021 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".