2021 CRS/CSWR Graduate Fellows Colloquium
Bibliographic record
Abstract
Graduate fellows for the Center for Southwest Research & Special Collections (CSWR) and Digital Initiatives & Scholarly Communication (DISC) for the 2020-2021 academic year present on their projects. The fellowships are sponsored by the Center for Regional Studies (CRS) and the Office of Graduate Studites. The presentations were divided into two days. Day 1, Tuesday, April 13, 2021 Annah Macha, Department of Language, Literacy, & Sociocultural Studies, PhD candidate An Investigation of the History of Admission of African- American Students at UNM, 1889-1975 Daejin Kim,Department of Linguistics, PhD candidate The 1970 Native American Census in New Mexico Bre Reiss, Department of Art, PhD candidate Curios and Revolutionaries: The History of Alice Gatliff Zonnie Gorman, Department of History, PhD candidate & Museum Studies minor William Dean Wilson, Navajo Code Talker Day 2, Thursday, April 15, 2021 Rachel Snow, Museum Studies, MA candidate Documenting the Now – Black Lives Matter Collection Ryuichi Nakayama, Department of Art, PhD candidate Antoine Predock’s Canadian Museum of Human Rights: Process of Materializing
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.503 | 0.282 |
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".