Innovation and Firm Performance. Econometric Explorations of Survey Data
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
Introduction A.Kleinknecht & P.Mohnen PART ONE: COMPARING INNOVATION INDICATORS Towards an Innovation Intensity Index: the Case of CIS-I in Denmark and Ireland P.Mohnen & M.Dagenais Innovations, Patents and Cash Flow P.Geroski, J.Van Reenen & C.Walters The Mutual Relation Between Patents and R H.van Ophem, E.Brouwe, A.Kleinknecht & P.Mohnen PART TWO: DETERMINANTS OF INNOVATIVE BEHAVIOUR Innovation and Farm Performance: The Case of Dutch Agriculture P.Diederen, H.van Meijl & A.Wolters Determinants of Innovative Activity in Canadian Manufacturing Firms J.Baldwin, P.Hanel & D.Sabourin Differences in Determinants of Product and Process Innovations: the French Case C.Le Bas & A.Cabagnols Differences in Determinants of Product and Process Innovations: the Spanish Case E.Martinez-Ros & J.M.Labeaga PART THREE: SPILLOVERS AND R&D COLLABORATION Innovation Without R&D? Public and Private Spillovers in the French Agro-Food Industry V.Mangematin & N.Mandran The Effect of Spillovers and Government Subsidies on R&D, International R&D Cooperation and Profits: Evidence from France F.Favre, S.Negassi & E.Pfister The Impact of Spillovers and Knowledge Heterogeneity on Firm Performance: Evidence from Swiss Manufacturing S.Arvanitis & H.Hollenstein Why do Firms Not Collaborate? The Role of Competencies and Technological Regimes A Leiponen PART FOUR: INNOVATION AND EXPORT PERFORMANCE Innovative Capabilities and Export Performance: A Study of Canadian Manufacturing SMEs E.Lefebvre & L-A.Lefebvre R&D and Export Performance: Taking Account of Simultaneity A.Kleinknecht & R.Oostendorp
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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