Bibliographic record
Abstract
This important multidisciplinary work is a vital addition to the field of porn studies.It contains contributions from scholars in a wide range of academic disciplines, including art history, ethnic studies, literature, and film and media.Its scope is quite broad and extends well beyond the traditional boundaries of archives, libraries, and museums.The essays are arranged in six separate sections.The first, "Pedagogical Archives," examines the structures in place for the creation of porn knowledge (universities and academia, archives, libraries, and museums), which enable the critical reception and discussion of porn.As its name implies, the section "Historical Archives" focuses on specific textual documents and key moments in the history of porn.The third section, "Image Archives," contains essays dealing specifically with porn in the form of photographs, visual arts, and film.The final three sections are thematic in scope.The fourth, "Rough Archives," looks at porn that contains depictions of imagined or real non-consensual sex.The fifth, "Transnational Archives," discusses porn from within other geographical borders (in this case, Puerto Rico and Brazil), as well as records that cross the boundaries of what traditionally qualifies as porn (specifically war porn, in which the theatre may be Iraq and Afghanistan, among other locations).The last section, "Archives of Excess," examines porn that falls
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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".