Innovation projects and visions on the future: ambition and commitment in the Agropark case
Bibliographic record
Abstract
Abstract Since the 1980s, Dutch agricultural policy focuses on changing the agricultural sector into a more sustainable sector. In this article we explore an Agropark visioning initiative and four Agropark innovation projects to provide further understanding in how visions on the future influence innovation projects. In addition we question which innovation strategies actors adopt to ensure both high levels of ambition and high degrees of commitment towards the innovation Agropark. Our study shows that future visions can lead to high expectation within the policy and public domain which creates both opportunities and tensions for innovation projects. Furthermore, the analysis shows that each Agropark innovation project applied specific innovation strategies that suited their distinct context and network of actors. Furthermore, actors within the innovation projects contextualise and thereby re-design future visions into local visions. They thus create a more viable design but at the same time dilute initial ambitions. Recognising these tensions and opportunities in their different guises, and making them part of the learning process time and again, both at regime level and at niche level, assist actors that aspire to guide far-reaching innovations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".