Bibliographic record
Abstract
Folklorists have studied the heritage and genealogy of various communities, so it is only fitting that a new history of the field of North American folkloristics should examine the genealogy of folklorists.While not quite a "biography" of the field, the 26 discrete articles in Folklore in the United States and Canada: An Institutional History, edited and with an introduction and conclusion by Patricia Sawin and Rosemary Lévy Zumwalt, examine the evolution and history of folkloristics as it evolved in 24 (mostly) graduate programs in American and Canadian colleges and universities.The volume's articles are divided into three sections.The first explores programs that emerged prior to the 1960s; the second looks at the prospering of folklore programs in the 1960s and 1970s, primarily at public Canadian and American universities.This section begins with a nostalgic article by Zumwalt on "'The Great Team' of American Folklorists: Characters Large in Life and Grand in Plans," in which she looks at the "young Turks" who became the "founding fathers" of the field in the 1960s (Stith Thompson, Richard Dorson, Alan Dundes, Dan Ben-Amos et al.).The collegiality and collaboration (in spite of some notable rivalries) that built the field emerge clearly in her essay.She points out that the team of American folklorists "did not develop from one center outward but was an interconnected flow of people and ideas among centers of folklore," each strengthening the others and being strengthened in turn (72).The third section looks at the period of innovation, reshaping, and diversity from 1980 to 2010.Thus, program descriptions run the gamut from the academic degree program in folklore and mythology at Harvard, established in 1967 by Albert Bates Lord (written by Rachel Kirby and Anthony Bak Buccitelli) to the recently founded (2007) community-oriented program in cultural sustainability at Goucher College (Amy E. Skillman and Rory Turner).The essays reveal an enormous variety in program structures: while some folklore programs are based in a department or institute of their own, others have found a home in related disciplinary departments (notably languages, ethnology, anthropology) and interdisciplinary programs (regional and area studies).None of the essays is long, yet each provides detailed documentation about the people who created the programs and taught in them, the challenges they faced, and the accomplishments they achieved.Many photographs of leaders in the field enhance the volume.No less important, the essays provide practical hints about how to win friends within the institution, get support from colleagues at other academic centers, engage in strategic thinking about program building, and negotiate with one's own administration for a place in the curriculum.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.028 | 0.008 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.000 |
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".