An Epidemic of Rumors: How Stories Shape Our Perceptions of Disease
Why this work is in the frame
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Bibliographic record
Abstract
An Epidemic of Rumors: How Stories Shape Our Perceptions of Disease. By Jon D. Lee. (Logan, UT: Utah State University Press, 2014. Pp. xi + 219, acknowledgments, introduction, epilogue, index, references. $26.95 paper, $21.00 e-book.)It turns out that epidemics are a laughing matter-and also a matter of conspiracy theory and rumor. In An Epidemic of Rumors: How Stones Shape our Perceptions of Disease folklorist Jon D. Lee sets out to show how perceptions of diseases were formed through the circulation of narratives during the SARS epidemic of 2003, and how these stories affected behavior. More broadly this book describes patterned ways communities tend to respond to the news of emerging diseases. Central to Lee's project is a desire to foster better communication between lay audiences and the expert knowledge disseminators of public health, media, and academic institutions. While such experts may scoff at or dismiss popular narratives about diseases, Lee examines lay beliefs with the experience-centered approach (as exemplified by David Hufford) that takes seriously the observations and reasoning skills of ordinary people. Many of the narratives shared among lay observers of epidemics manifest xenophobic fears, and Lee shows that though experts may deride popular rumors they are often partially responsible for propelling problematic messages that exacerbate fear and suspicion.An Epidemic of Rumors begins with a meticulous timeline of the public health sector's, the media's, and (to a lesser extent) the medical research community's responses to SARS as they unfolded between April and July of 2003. Lee relies heavily on media sources to construct the timeline, a strategy that illuminates some processes more than others. The mass media's extraordinary ability to distill information from the scientific community for lay audiences makes them an important go-between. At the same time the media's tendencies to oversimplify, distort information, and inundate the public with sensationalist headlines created the context for public panic and the temporary collapse of the tourist industry in SARS hotspots in Asia and Canada. Thus public health reports are the building blocks of rumor and conspiracy theory spread via news media, internet, and word of mouth.The chapters that follow plunge the reader into the scholarship on and content of folk discourses of disease. Primarily the focus is on rumors and conspiracy theories about the origins and spread of diseases. Lee ranges himself among scholars of folklore and cultural studies (including Diane Goldstein, Patricia Turner, Charles Briggs, and Gary Alan Fine) and shows how SARS rumors borrow heavily from the template of other epidemic rumor cycles. The usual suspects of animal origins or outsiders are blamed for spreading the disease. Rumors and jokes about diseases have the power to naturalize the connection between racial categories and particular diseases. …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it