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
AbstractThis thesis builds on contemporary observations of a qualitative change in the way research and development (R&D), invention and innovation activities take place: an increasingly open, distributed or network-like character of innovation activities with the locus of innovation shifting from an individual entrepreneur to hybrids, consortia or networks (Bouba-Olga & Grossetti, 2007; Laursen & Salter, 2006; Chesbrough, 2006, 2003; Powell & Grodal, 2005; Gassmann & Enkel, 2005; Coombs et al., 2001; Powell & Brantley, 1992); an increasing geographic reach of innovation activities, and a geographic topography best characterised as 'local nodes in global networks' (Belussi et al., 2010; Cooke, 2008; Moodysson, 2008; Coenen, 2006; Asheim & Gertler, 2005; Bathelt et al., 2004). Increasingly, innovation activities take place on different geographic scales, combining the best of local resources and expertise with global ones. Moreover, geographic scope has broadened from the traditional research countries (North America, Canada, Europe and Japan) to newcomers, particularly Russia, India, China and, to a lesser extent, Brazil (the BRICs) (Boekholt et al., 2009; Howells, 2008; UNCTAD, 2005). KeywordsInnovation ActivityInteractive LearningSpot MarketEmpirical PartOpen Innovation ProcessThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.015 |
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