Earth Resource Management, a New Graduate Degree at the University of Utah
Bibliographic record
Abstract
Earth’s resources can be considered in three categories: captured or reusable—sun, wind, rain, tides, etc.; nurtured or renewable—ecosystems, including soils, plants, animals, etc.; and extracted—mineral deposits, including oil and gas. All three types of resources are used by humans for sustenance and for improvement of the quality of life. Increasing human population and the continuing extraction of depletable resources may lead to shortages of key commodities, unbalanced markets with wide price swings, and economic depression in areas where those resources are depleted. In addition, some resources may be used or extracted without adequate consideration of the influence of that use on other resources. Until recently, all of the earth’s resources were treated as infinite, and the use of those resources proceeded accordingly. In particular, mineral resources were often “high graded” with little thought of the resultant influences on other resources. For true sustainability, an integrated, holistic approach to resource usage must be developed and implemented. That approach will necessarily incorporate the knowledge and methods of the sciences, engineering, business, law, and humanities, and will include five important components: people, resources, innovation, cooperation, and leadership. At the University of Utah, the College of Mines and Earth Sciences is preparing to offer a master’s degree in Earth Resource Management. This course of study will be one of the options in the accredited Professional Management of Science and Technology program, administered by the University’s Graduate School. It is designed to prepare professionals competent in all of the aspects of sustainable resource management.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.097 | 0.024 |
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".