Bibliographic record
Abstract
The National Association of State Boards of Geology (ASBOG®) was founded in 1988 to provide oversight and coordination for state licensing boards for the geosciences. Currently, 30 states and Puerto Rico are members of ASBOG, which has coordination responsibility for approximately 40,000 licensees. Twice a year, two examinations, Fundamentals of Geology and Practice of Geology, are administered by ASBOG to evaluate the qualification of candidates for licensing in the member states. The exam content is driven by surveys of the practicing licensed professionals and academicians [Williams et al., 2012]. Professional ethics is regarded as extremely important by survey responses of all components of the geoscience community, including practicing licensed geologists in Canada and the United States, and members of the academic community. There is general agreement among these practitioners as to the relative importance of different elements of professional ethics and the frequency of these issues encountered in daily activities. Comparison of results of the surveys between administrations in 2010 [Warner and Warner, 2010] and 2015 [Warner, 2015] indicate little change in the attitudes of practicing geologists toward professional ethics. Recognizing the importance of professional ethics in the geosciences, ASBOG is promoting the inclusion of professional ethics in the college geoscience curriculum in addition to encouraging the instruction of practicing professionals [Williams, 2013; Williams, 2014].
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.014 |
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".