Interdisciplinarity/Extradisciplinarity: On the University and the Active Pursuit of Community
Bibliographic record
Abstract
This paper explores a defining contradiction at the heart of the university as a social and cultural institution: society requires the university to serve it, but this service requires the university's detachment and freedom from external social determinations. I argue that we can see this paradox embedded at the very heart of the university expressed in a myriad of ways throughout the institution's long history, including the relatively recent debates about interdisciplinarity. I review some instances in the history of the university where this contradiction has expressed itself most clearly and then examine some of the ways in which the rubric interdisciplinarity has been deployed in the contemporary corporate university. How is the term used? Who uses it and for what reasons? How might we come to understand interdisciplinarity as a performative term re-presenting or promising one set of meanings, but instantiating a very different set of actions? What are the political dimensions of its use? I highlight and problematize the distinction between the emergence of interdisciplinarity as an intellectual phenomenon and interdisciplinarity as it is currently defined and administered within academic institutions. Finally, I explore an alternative way to think about what we do at the university in the name of interdisciplinarity.
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.083 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.005 | 0.005 |
| 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".