If you are for market creation, you should be for market destruction! Ethics and the relations between exnovation and innovation for changing direction
Bibliographic record
Abstract
While innovation and market creation have long received attention for changing the direction of socio-economic development, exnovation and market destruction have received such attention only recently. Rather than assuming innovation and exnovation to be simply two sides of creative destruction processes, we aim to balance the discussion by exploring normative arguments in relation to both innovation and exnovation. We show how instrumental and enabling arguments for changing direction also apply to exnovation. By distinguishing three scenarios – complementation, reversion and reduction – we show that these arguments support genuine creative destruction in the case of a complementary innovation-exnovation relation. In addition, we show that they support an independent focus on exnovation, where the latter relies on reversion to old technologies or on overall reduction of economic activity. We discuss the role of freedom across exnovation processes, and the implication of our analysis for directing societal change without reducing democratic possibilities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.046 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".