Evidence for Free Innovation
Bibliographic record
Abstract
In this chapter I present evidence that free innovation is a very substantial phenomenon with respect to the development of products consumed within the household sector.As we will see, today tens of millions of consumers annually spend tens of billions of dollars creating and modifying products to better serve their own needs.In fact, aggregate household sector product development expenditures rival the scale of business sector expenditures by producers developing products for consumers.Next, we will see that more than 90 percent of the developers of product innovations in the household sector meet both of the criteria for free innovation specified in chapter 1: the innovators develop their innovations during their unpaid, discretionary time; and they do not actively protect their designs from free adopters.The remainder are aspiring entrepreneurs.Finally, I explore the nature of transaction-free self-rewards central to the viability of free innovation, and discuss why it can make economic sense for free innovators to reveal their innovations for free. Six National StudiesAt the time of this writing, six national surveys have explored the scale and scope of household sector product innovation by product users.I begin with a very brief overview of the methods all these studies used.Full details will be found in the published reports on each.The six national surveys were carried out in the United Kingdom by von Hippel, de Jong, and Flowers (2012), in the United States and Japan by Ogawa and Pongtanalert (published in von Hippel, Ogawa, and de Jong 2011), in Finland by de Jong, von Hippel, Gault, Kuusisto, and Raasch (2015), in Canada by de Jong (2013), and in South Korea by Kim (2015).All six study samples included only new products and product modifications that had been developed by household sector individuals for 2Evidence for Free Innovation
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".