Bibliographic record
Abstract
Alice Walker once exhorted her audience, “Stand up, speak out, and get beside yourself! ” Her amusing urging was by way of saying women should stop sniveling. Once in a while they should even try being outrageous. They should get beside themselves. “Beside ” is an interesting preposition. Eve Sedgwick (2003) comments “there is nothing very dualistic about [beside]” (8). “Beside ” is friends with “with ” rather than “or, ” and encompasses a wide range of emotions that some might consider outrageous, like mimick-ing, aggressing, warping, twisting, repelling, and paralleling (8). Sedgwick’s sideways celebration gives a wide berth to what it means to be human. Her argument and culminates in a discussion of the queer-identified performance known as “camp. ” “Camp ” has usually been seen as a form of parody that seeks to expose the assumptions of the dominant culture. Disagreeing with this characterization, Sedgwick sees camp as not just critical of culture but as acting along side it in order to be “additive and accretive ” (149). Her descriptive use of language defending this point mirrors the sense of am-
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 | 0.012 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.068 | 0.037 |
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".