Developing a living lab in ethics: Initial issues and observations
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
Living labs are interdisciplinary and participatory initiatives aimed at bringing research closer to practice by involving stakeholders in all stages of research. Living labs align with the principles of participatory research methods as well as recent insights about how participatory ways of generating knowledge help to change practices in concrete settings with respect to specific problems. The participatory, open, and discussion-oriented nature of living labs could be ideally suited to accompany ethical reflection and changes ensuing from reflection. To our knowledge, living labs have not been explicitly trialed and reported in ethics literature. In this discussion paper, we report and discuss four initial issues that marked the process of setting up a living lab in ethics: (1) determining the goals and expected outcomes of an ethics living lab; (2) establishing operational procedures; (3) selecting communities and defining pilot projects; and (4) adopting a lens to tackle emerging questions and challenges. We explain these four issues and present the paths taken based on the novel and specific orientation, that is, living ethics, at the basis of this project. In alignment with living ethics and É-LABO, we approach challenges as learning opportunities to ask not only "how" questions but also "why" questions. We hope that this discussion paper informed by our experience helps to clarify the theoretical, methodological, and practical approaches necessary to successfully adopt and employ living labs in ethics.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it