When desirability and feasibility go hand in hand: innovators’ perspectives on what is and is not responsible innovation in health
Bibliographic record
Abstract
While the conceptual foundations of Responsible Research and Innovation (RRI) were consolidated in the past decades, the practice of RRI remains poorly understood. The goal of our study was to gather the practical insights of professionals who design, develop and commercialize health innovations. We invited Canadian engineers, industrial designers, clinicians and entrepreneurs (n = 31) to visit a website describing nine innovations that possessed attributes of the Responsible Innovation in Health framework and to explain whether these examples illustrated important attributes of responsibility or not. Our qualitative analyses clarify how these innovators pondered whether: (1) stakeholder involvement is responsible; (2) businesses can behave responsibly; (3) innovations should adapt to health systems; and (4) the environment matters in health innovation. This study shows that innovators generally agree on the desirability of several responsibility principles, but identify feasibility issues that call for attention if RRI is to be meaningfully implemented in the health field.
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 | 0.059 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 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; both teacher heads agree on what is shown here.
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".