Policy mixes for sustainability transitions: New approaches and insights through bridging innovation and policy studies
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
There has been an increasing interest in science, technology and innovation policy studies in the topic of policymixes. While earlier studies conceptualised policy mixes mainly in terms of combinations of instruments to supportinnovation, more recent literature extends the focus to how policy mixes can foster sustainability transitions. For this,broader policy mix conceptualisations have emerged which also include considerations of policy goals and policystrategies; policy mix characteristics such as consistency, coherence, credibility and comprehensiveness; as well aspolicy making and implementation processes. It is these broader conceptualisations of policy mixes which are thesubject of the special issue introduced in this article. We aim at supporting the emergence of a new strand ofinterdisciplinary social science research on policy mixes which combines approaches, methods and insights frominnovation and policy studies to further such broader policy mix research with a specific focus on fostering sus-tainability transitions. In this article we introduce this topic and present a bibliometric analysis of the literature onpolicy mixes in both fields as well as their emerging connections. We also introduce five major themes in the policymix literature and summarise the contributions made by the articles in the special issue to these: methodologicaladvances; policy making and implementation; actors and agency; evaluating policy mixes; and the co-evolution ofpolicy mixes and socio-technical systems. We conclude by summarising key insights for policy making.
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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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