Bibliographic record
Abstract
Though not Basque himself, Casey Kennington grew up on a dairy farm in rural Ontario, Oregon, U.S.A., where he first heard the word "Basque" and and met many Basques, including a high school teacher who helped him foster a love for computers. During his university studies, he spent extended amounts of time in Japan, France, and Germany, learning the languages of each country. Since 2016, Casey has been a faculty member of the Department of Computer Science at Boise State University, focusing his research on dialogue systems and natural language processing. His love of languages led him to learn about the Basque language, and, despite being a busy professor, take two semesters of Basque in 2021-2022 at Boise State University. While attending a conference in the Basque Country in 2023, he more deeply understood how unique the Basque people are and why their language is worth learning and preserving. Education Ph.D. - Linguistics - Bielefeld University, Germany, 2016 MS - Cognitive Science - Nancy, France, 2011 MS - Computational Linguistics - Saarbrücken, Germany, 2011 BS - Computer Science - Brigham Young University, 2007 ORCID: https://orcid.org/0000-0001-6654-8966
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".