Opening design and innovation processes in agriculture: Insights from design and management sciences and future directions
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
Research has identified an urgent need to renew agriculture's traditional design organization and foster more open, decentralized, contextualized and participatory approaches to design and innovation. While the concepts of co-design and co-innovation used in agriculture resemble features of open innovation, they may benefit from ‘inbound open innovation’ themselves through cross-fertilization with management studies, design science, science and technology studies, and organization studies. This special issue brings together different streams of research providing novel perspectives on co-design and co-innovation in agriculture, including methods, tools and organizations. It compares empirical experiences and theoretical advances to address a variety of issues (e.g., innovation ecosystems, collective design management, participatory design methods, affordances of system analysis tools and network leadership) that shed new light on co-design and co-innovation in support of sustainable agriculture and more broadly transitions towards a diversity of food systems and a circular bioeconomy. This introductory paper presents crosscutting insights and distills from these three directions for future research and practice in agricultural design and innovation: 1) Further opening design and innovation techniques and tools to better account for visual, auditory, tactile and olfactory expressions in evolving designs and what they afford users; 2) Further opening innovation networks in view of creating and stimulating integrative niches that can foster sustainability transitions, which also requires network managers instilling a reflexive stance of network members and broader awareness of power structures attached to organizational, sector and paradigmatic silos in agricultural systems; and 3) Further opening the range of innovation actors to include non-human actants to better account for the agency of the material and ecological.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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