Acknowledging complexity: Critically analyzing context to understand interdisciplinary research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is timely to develop improved understandings about strengthening interdisciplinary contexts to guide effective and quality healthcare research; contexts in which health and social issues occur do not recognize disciplinary boundaries. Similar to the notion of "partnership", the terms multidisciplinary, interdisciplinary and transdisciplinary are in danger of becoming conceptually indistinct and thus of limited usefulness for researchers, practitioners and teams. In this paper, we review basic concepts related to cross-disciplinary relationships as well as common arguments for and against interdisciplinary research. We then extend this critique by adding considerations of the influence of context, specifically social and spatial influences on interdisciplinarity. In doing so, we advocate the need for research that explicitly acknowledges complexity and considers context to advance understanding of effective interdisciplinary research.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it