The impact of the EU Industrial R&D Investment Scoreboard on science and policy
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
Abstract The EU Industrial research and development (R&D) Investment Scoreboard (Scoreboard) provides data and economic analysis to monitor corporate R&D and inform EU policy since 2004. This study investigates the influence of this annual report on both science and policy. Our findings reveal that while the Scoreboard has been more frequently cited in policy documents than in peer-reviewed papers, academic interest is growing. In policy, it has influenced the EU policy narrative regarding the EU corporate R&D intensity gap relative to its competitors. In science, citations are more often linked to specific analytical insights of the reports than to the underlying data. However, studies combining Scoreboard and patent data receive relatively more citations, highlighting the value of integrating diverse data to better understand innovation dynamics. Interestingly, policy documents citing the Scoreboard exhibit a shorter citation time window than academic papers, reflecting its immediate relevance to policy debates.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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