‘What do you mean?’ The importance of language in developing 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
Unity between human and physical geography continues to be debated widely. However, if geography is to take advantage of its unique positioning between the natural and social sciences, geographers need to be able to communicate more effectively and efficiently across human and physical specialisms. In this paper we focus on the significance and uses of language in interdisciplinary research practice. Interdisciplinary research faces a range of challenges in achieving effective communication between discipline‐based experts, of which language is key. This paper draws on a discussion developing the initial ideas for a research application and a field day to familiarize the group members with the study area. Dialects , metaphor and articulation are identified as three overlapping aspects of language which play an important role in developing understandings between different disciplines. These three different aspects of language are illustrated through the analysis of three situations focusing on the words dynamic , mapping and catchment . We conclude that interdisciplinary projects must allocate time to the development of shared vocabularies and understandings. Common understanding derived from shared languages in turn plays a vital role in enhancing the relations of trust that are necessary for effective interdisciplinary working.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it