The Complexities of Interdisciplinarity: Integrating Two Different Perspectives on Interdisciplinary Research and Education
Bibliographic record
Abstract
The aim of this article is to open a conversation between the complexity & education community and the field of interdisciplinarity (as well as its close relative, interprofessionalism). It starts by describing two very different streams of thought in the literature on interdisciplinary research and education: One that focuses on the socio-cultural dynamics among disciplinary ‘knowers’ and one that emphasizes the complexity of the phenomena studied by these disciplinary knowers. Next, the author argues that recent epistemological thinking associated with the complexity & education community can help to integrate these streams of thought—offering a way for interdisciplinary inquiry to respect both the complexity of knowers and the complexity of the known.
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 | 0.037 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.011 | 0.113 |
| Scholarly communication | 0.037 | 0.054 |
| Open science | 0.003 | 0.028 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".