Porn Vilification and Age Verification: Regulating Online Pornography and Sex Work
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: This commentary presents regulatory mechanisms recently proposed or passed by countries around the world requiring providers of online pornography to implement age-verification technologies. Canada's "Protecting Young Persons from Exposure to Pornography" Act (PYPEPA) is presented as a key exemplar of the problematic discourses used to construct pornography and sex work as dangerous that contribute to the creation of harmful and ineffective legislation with far-reaching consequences for the sex work community. PYPEPA and other presented legislation demonstrate a pattern of moralistic policies rooted in problematic discourses and fundamental misunderstandings of the sex work industry, which persist despite evidence of their growing harm. This problematic framing of online pornography creates a perceived need for the government to "do something", resulting in punitive policies that have far-reaching consequences. While proponents of these bills are attempting to reduce the potential for harm on children who access to online pornography, the stated goals of the legislation suggest that they are unnecessarily concerned with defining acceptable categories of sexuality. Alternatives to the vilification of online pornography, with the mutually-aligned goal of limiting the potential for harm, are explored as a better way forward.
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.
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 | 0.000 |
| 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