Bibliographic record
Abstract
This chapter examines the “Satanic Panic” of the 1980s, a period marked by widespread fears over devil-worship and Satanic rituals. It was most pronounced in the United States, but also affected parts of Canada, the United Kingdom, Australia and South Africa. The panic largely manifested as dozens of accusations of “Satanic ritual abuse,” particularly against suburban daycare centre workers, many of whom spent years or decades in prison before being exonerated. It also included fears of demonic possession, devil-worshipping cults and Satanic influences that allegedly reached into the highest echelons of corporate power, especially in the music industry. Anxieties were exacerbated and reinforced by the culture&s;s increasing amount of sensational news media content, especially in its televised format, and its symbiotic relationship to horror films, heavy metal music and conservative political, religious and economic policies. A feedback loop between media and public fears was created, igniting a pervasive moral panic over the alleged threat of Satanism, especially regarding the safety of children. The panic underscores how media, entertainment and conservative agendas amplified and perpetuated public fears, leading to significant social and legal consequences. It serves as a powerful example of the media&s;s role in shaping and distorting public perceptions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".