Bibliographic record
Abstract
Theory at its best should be a kind of friendship. Thinking is something one does on one's own; but having thought one's way to a set of theoretical positions, one exposes those intellectual commitments to the test of seeing how they stand up to friendly but challenging scrutiny. I'm grateful for the critical commentaries on my book featured in this symposium because they seem to me to have generated interesting and thoughtful responses to what I have written; but I'm no less grateful because they also nicely exemplify this spirit of dialogical friendship. In that way, they help to vindicate the enterprise of theory as I have just characterized it. These theorists are also my friends, and the friendship is constitutively grounded in a shared commitment to theory as a vocation.
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 | 0.052 | 0.119 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.021 | 0.027 |
| Scholarly communication | 0.026 | 0.016 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.029 | 0.070 |
| Insufficient payload (model declined to judge) | 0.005 | 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".