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 Both theoretical and conceptual understanding of innovation has developed significantly since the early 1980s. More noticeable, however, are the major changes that have been experienced in empirically‐oriented innovation research as a result of the introduction of firm level innovation surveys. Collecting innovation related data via firm based surveys has now become a common practice for many countries for example, Canada, United States, Malaysia, Taiwan, Australia, New Zealand as well as almost all EU countries. These survey‐lead approaches have transformed our understanding of the nature and determinants of innovation and also increased our understanding of the role played by innovation in growth. At the same time, the surveys themselves have also been adapted as our conceptual understanding of innovation has increased. As such, the balance of innovation‐related research has shifted from a theoretical to a primarily empiricist‐lead agenda, and increasingly combined both quantitative and qualitative approaches. The objective of this paper is examine how our understanding of innovation has evolved over the last few decades, to identify the major theoretical and empirical influences on our understanding, and to assess the role which innovation surveys have played in this evolution.
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 | 0.033 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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