Bibliographic record
Abstract
Illustrated with numerous stories collected from Alaska, the Yukon, and South Africa and further enlivened by the author's accessible style and experiences as a longtime oral historian and archivist, So They Understand is a comprehensive study of the special challenges and concerns involved in documenting, representing, preserving, and interpreting oral narratives. The title of the book comes from a quotation by Chief Peter John, the traditional chief of the Tanana Chiefs region in central Alaska: "In between the lines is something special going on in their minds, and that has got to be brought to light, so they understand just exactly what is said." William Schneider discusses how stories work in relation to their cultures and performance settings, sorts out different types of stories-from broad genres such as personal narratives and life histories to such more specific and less-often considered types as presentations at hearings and other public gatherings-and examines a variety of critical issues, including the roles and relationships of storytellers and interviewers, accurate representation and preservation of stories and their performances, understanding and interpreting their cultural backgrounds and meanings, and intellectual property rights. Throughout, he blends a diverse selection of stories, including his own, into a text rich with pertinent examples. William Schneider is curator of oral history and associate in anthropology at the Rasmuson Library, University of Alaska Fairbanks, where he introduced oral history "jukeboxes," innovative interactive, multimedia computer files that present and cross-reference audio oral history and related photos and maps. Among other works, his publications include, as editor, Kusiq: An Eskimo Life History from the Arctic Coast of Alaska and, with Phyllis Morrow, When Our Words Return: Writing, Hearing, and Remembering Oral Traditions of Alaska and the Yukon.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.071 | 0.035 |
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".