Embedding Librarians in Archaeological Field Schools
Bibliographic record
Abstract
Abstract Participating in an archaeological field school is one of the only educational experiences that nearly all professional archaeologists have during their training. As a result, field schools are uniquely suited to provide experiential education in emerging skills that all archaeologists will need, such as information and data literacies at all stages of the contemporary research and publishing cycle. The “embedded” librarian program in the University of New Brunswick's Downeast Maine Coastal Archaeology Field School is an effective means to deploy that focused expertise to help students better understand the relationship between fieldwork, data, and dissemination. At the same time, being in the field provides librarians with the knowledge to respond more effectively to the complex data management and research needs of archaeologists. We encourage large research projects to consider librarians as specialist members of the research team.
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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 | 0.058 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.031 | 0.023 |
| Open science | 0.006 | 0.036 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.054 | 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".