INVERTING IMAGE AND REALITY: R. V. SHARPE AND THE MORAL PANIC AROUND CHILD PORNOGRAPHY
Bibliographic record
Abstract
In the atmosphere of high anxiety surrounding the Supreme Court’s decision in R. v. Sharpe, abnormal and normal collide and fantasy and representation become equated with reality. It is my intent in this short article to explore the complex cultural and political conditions that give meaning to the Supreme Court’s unanimous endorsement of stiff criminal penalties for possessing sexual representations of adolescents and children. In the Criminal Code provisions on child pornography and in the discursive web woven by both the majority and minority opinions in Sharpe, anxieties about the well-being of children are being projected onto the highly symbolic target of child pornography. Any dissent is pathologized and cast into what has become an elastic category — “the pedophile.” As Weeks writes, “[m]oral panic occurs in complex societies when deep rooted and difficult to resolve social anxieties become focussed on symbolic agents that can be easily targeted.”2 There is strong evidence that we are in the midst of a moral panic around child pornography, the contours of which require careful analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".