In Search of Transdisciplinarity: A Review of Two Workshops Supported by Situating Science
Bibliographic record
Abstract
Disciplines have a way of imprisoning their creations. Entrenched in an incommensurable discourse, ideas grow stagnant. Whether ideas transcend this imprisonment is a matter of adapting, flexing, and mobilizing knowledge. This is the aim of Situating Science: Cluster for the Humanistic and Social Studies of Science. Promoting transdisciplinarity among researchers, stakeholders, and the public, the Cluster brings diverse groups of scholars to sit around a common table and discuss a common theme. My aim in this short review is to capture some of the central themes and discussions of two such workshops, one on empathy, the other evidence-based medicine. Both workshops provided a fascinating multidisciplinary perspective on topics that easily transcend disciplinary boundaries. Yet the divisions between participants were clear, leaving some discouraged about producing collaborative work. As both workshops boasted a broad range of speakers and participants, my challenge has been to identify common themes without diminishing or disregarding this multiplicity of perspectives. I have only sought to highlight some of the most thought-provoking ideas.
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 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 | 0.021 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".