Bibliographic record
Abstract
This paper examines a 1996 U.S. internet censorship protest that encouraged users to email a series of technically “indecent” files as attachments to Speaker of the House Newt Gingrich using an online email generator. These attachments were: a list of abortion clinics, a graphic illustration of condom-use instructions, and excerpted sexually explicit scenes from Gingrich’s own novel, 1945. Selecting from a drop-down menu, senders chose their attachments, completed a personalized message, and clicked send, all within a web-based form. By using the platform to inundate the Speaker’s email with attachments, senders cleverly broke the censorship provisions of the 1996 Communications Decency Act (CDA), putting themselves at risk to the criminalization of sexual expression online. The “bad attachments” protest grew out of the fact that online information about sexuality was vital to marginalized communities with limited access to other kinds of information channels—including queer and rural youth, and people living with HIV. This paper argues that the protest attachments constitute a queer, material digital practice, attuned to the political demand for ready information access as a means of survival.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".