Bibliographic record
Abstract
Our varied communities of discourse face a rhetorical future shaped by juridical styles reminiscent of the "adversary culture" postulated by post-war American critic Lionel Trilling. Itself the subject of litigious debate. the adversarial spirit today shows few signs of weakening, but its influence can be better understood and guided along certain tracks. To influence this adversarial style in coming decades, we need to explore the difference between evidencebased reasoning, which draws on the sensationalist logic ofinduction. and reflexive reasoning, which draws on the second-order logic of presumption. Understanding the structures and dynamics of this reflexive style forces us to address our responsibilities as speakers, as we seek to shape our rhetorical future. Close examination of adversarial contlict may lead us toward useful consensus on how the new game should be played.
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 | 0.028 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.019 | 0.047 |
| Scholarly communication | 0.024 | 0.019 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".