Bibliographic record
Abstract
Once Upon a Virus: AIDS Legends and Vernacular Risk Perception. By Diane E. Goldstein. (Logan: Utah State University Press, 2004. Pp. xvi + 210, acknowledgments, introduction, illustration, bibliography, indices. $39.95 cloth, $19.95 paper) Once Upon a Virus is an essential work, a masterful study showing that contemporary legends at once reflect and embody vernacular perception of AIDS. Using information from a variety of sources (including interviews, questionnaires, and news reports), placing interpretation squarely in contemporary legend scholarship, and writing in a clear, respectful style, Diane Goldstein offers a treatise that is a model for research and writing not only for AIDS legend scholarship, but for scholarly work in general. As Erika Brady exclaims on the back of the book, This is an important book! The research area was Newfoundland, in the Canadian maritime provinces, but as a valuable addition to the literature on public health, belief, and narrative, this book's findings could apply anywhere. The impetus for it came from a sudden inexplicable upswing in the rate of AIDS infections in the province in the early 1990s. Goldstein begins with a look at the folklore of contagion, showing that childhood folk expressions of fear of contagion can be transmogrified into contemporary legends circulated among adults. Contemporary legend-unsubstantiated narratives with traditional themes and modern motifs that circulate in multiple versions and are told as if they are true or at least plausible (Turner 1993:5)-is a commentary on such current issues as health, crime, big business, government power, or sexuality. . . . Contemporary legends make the extraordinary ordinary and the ordinary extraordinary by combining common situations and events with unusual complications or results (25-26). In the Newfoundland AIDS legends, the antagonist is either a returned former resident of the area or a foreigner, whether from the Canada mainland, Europe, or the United States, who brings the disease into a community, sometimes by conscious infection through sexual activity and sometimes by means of a sinister agent such as a needle lodged in a movie theater seat or placed in a pay-phone change tray. The legends are not about the disease itself so much as they are about public perception of risk for becoming infected with the disease. Goldstein explores risk perception through several case studies derived from her Newfoundland fieldwork, each comprising a chapter of the book. …
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".