Bibliographic record
Abstract
In Queer Traffic, Jennifer Tyburczy traces how sexual dissidents across the Mexico-Canada-US borderlands transport the objects and experiences that nourish their sexual and social lives. She situates the North American Free Trade Agreement (NAFTA) as a pivot point in the formation of panics aimed at stamping out these outlaw sex practices. Highlighting NAFTA’s erotic investments in hetero- and homonormativity, racial capitalism, markets of dispossession, and neocolonialism, Tyburczy directly engages with art, activism, and archives to revisit the struggles of people who invented circuits of sexual exchange through four decades of violence and criminalization. In conversing with actors from bureaucrats to pornographers and in studying choreographies, social movements, and street vocabularies, she examines an array of tactics that undermine the market logics of trade law and policy. Dreaming of other forms of living that go beyond mere survival, Queer Traffic guides us through the renegade pathways that circumvent the seemingly endless reach of free-trade capitalism toward other routes to pleasure.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.140 | 0.019 |
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".