Classifying Innovation: An Ontological Framework and Data-Driven Approach for Measuring Radicalness in the Front End of Innovation Management
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
Idea evaluation has emerged as a pivotal aspect of creative thought and innovation processes, drawing increasedattention from researchers and managers. Despite the lack of consensus on a precise definition of innovation, there is a clear understanding that radical innovation significantly differs from incremental innovation. However, techniques for evaluating and selecting radical ideas have often been adapted from methods designed for incremental innovation or creative thought processes. This thesis establishes a framework to differentiate between radical and incremental innovations. Starting with foundational definitions, we examine traditional methods for evaluating innovative ideas. The core of our research introduces a novel Innovation Ontology and we demonstrate the capability to distinctly classify incremental and radical innovations, presenting a predictive model that generates a ‘radicalness’ score, thereby enhancing the precision and effectiveness of innovation management.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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