What Is Innovation? A Review of Definitions, Approaches, and Key Questions in Human and Non-human Innovation
Bibliographic record
Abstract
Abstract Innovation, new or modified learned behaviour, is core to cultural evolution and fundamental to the success of humans. Innovations allow us to adapt to and change habitats, solve novel problems, and survive and flourish in diverse environments. Innovation also appears to be pervasive across the animal kingdom, with adaptive importance within a wide range of species. This chapter covers how innovation and its subcategories are defined and studied and its importance to both cultural and genetic evolution. The authors discuss the difficulty of creating useful, operational definitions that can link disparate fields, and controversies in the study of innovation, such as the independence of innovation from processes such as exploration and creativity. Considering costs and benefits to innovation, the authors address how individual, social, and ecological influences shape innovative propensities. The chapter finishes by discussing how cross-disciplinary research is key to resolving controversies within the field.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".