Bibliographic record
Abstract
Internet health—here, the public use of information Web sites to facilitate decision making on matters of health and illness—is a rhetorical practice, involving text and trajectories of influence. A fulsome account of it requires attention to all parts of the rhetorical triangle—the speaker, the subject matter, and the audience—yet most scholarship on Internet health focuses on the speaker only: it typically raises concerns primarily about the dangers of unreliable sources, suggesting that, where speakers are reliable and information is accurate, Internet health simply empowers patients. This essay turns attention to the other elements of the triangle. It argues that health information is a complex entity—not only transmitted but also transformed by the Web—and, further, that Internet-health users are a complex audience—not only informed but also transformed by the Web. Rhetorically-minded researchers are well positioned to study not simply the informed patient but rather, more comprehensively, the wired one.
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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.043 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".