Sustainability Research and Interactive Knowledge Generation
Bibliographic record
Abstract
Based on experiences from the GreenRegio research project that investigates framework conditions for innovations in sustainable/green building, this working paper explores the potential of interactive and collaborative methods for knowledge generation and co-production. Engagement with local practi-tioners, private industry, academics, political decision-makers and representatives of the non-profit sector early on in the research process allows researchers to gain better understanding of the re-search object and context. It also creates a platform for (mutual) knowledge exchange. Methodologi-cally, the project incorporates interactive workshops and Delphi-based feedback and validation rounds, that – over the lifespan of the project – offer a mutual learning process further inspired by in-sights and experiences across four case studies in Europe, Australia, and Canada. The exchange and learning processes provide important insights on different forms and pathways of sustainability transi-tions in the building sector to all participants involved in the project, researchers and researched alike.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".