How qualitative criteria can improve the assessment process of interdisciplinary research proposals
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
Abstract Despite the increasing recognition for the scientific and societal potential of interdisciplinary research, selection committees struggle with the evaluation of interdisciplinary proposals. Interdisciplinary proposals include a wider range of theories and methods, involve a more diverse team, pose a higher level of uncertainty, and their evaluation requires expertise from multiple disciplines. In this study, we investigate the possibility to support the evaluation of interdisciplinary research proposals with measures of interdisciplinary research quality. Based on the literature, we curated a set of qualitative criteria and bibliometric indicators. Subsequently, we examined their feasibility using interviews with interdisciplinary researchers and a re-assessment session of a grant-allocation procedure. In the re-assessment session members of an original evaluation panel assessed four original research proposals again, but now supported with our measures. This study confirmed the potential of qualitative criteria to assess the interdisciplinarity or research proposals. These indicators helped to make explicit what different people mean with interdisciplinary research, which improved the quality of the discussions and decision-making. The utility of bibliometric indicators turned out to be limited, due to technical limitations and concerns about unintended side effects.
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 | 0.192 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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