Rethinking How Humanities Think: Daring and "do / make / think"
Bibliographic record
Abstract
Whether the administrative organization of people in the humanities takes the form of a department of English, philosophy, history, or comparative literature, etc., in the modern university, humanistic disciplines continue to reflect the institution in which they reside, even as that institution submits them to "two cultures," "science wars," or corporatization. Neither disciplinary distinctiveness, group identity, nor solidarity within the humanities as a division protect these forms of inquiry and exchange against dominant institutional imperatives and incursions. As a traditional container for academic activity, departments contribute to what is increasingly becoming a black box nexus of activity around the individual players: the black box being a reduction of a complex process to simply its inputs and outputs with the box around process itself.
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 | 0.020 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.025 | 0.224 |
| Scholarly communication | 0.041 | 0.024 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 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".