Benoît Godin, “Making Science, Technology and Innovation Policy: Conceptual Frameworks as Narratives”

Godin examines a number of “conceptual frameworks” used by science and technology policy makers in the United States and Europe from the 1930s to the present. He identifies eight such frameworks (or “frames”), arranged in three successive generations. The first, articulated from within the academy, included a theory of “Cultural Lags” between material culture (the culture of innovation) and adaptive culture (the users of technology), as well as the “linear model of innovation,” which suggests that innovation follows a linear sequence from basic research to applied research to development. The second generation fleshed out the linear model by positing a statistical correlation between research and economic growth, research and productivity, and research and industrial competitiveness. The basic structure of each of these frameworks is input-output based (and thus linear): in each case, more R&D money is directly correlated with an increase in the respective output. The third generation presented alternatives to the general linear model. The “National Innovation System” posited innovation itself as the goal of research, and characterized both innovation and research as systems involving many sectors, such as government, university, and industry. The “knowledge-based economy” framework sees knowledge as vital to both society and the economy, and thus makes it, in all its forms, a top priority. Godin notes that “knowledge” is too fuzzy of a concept to provide much in the way of content for this frame. Similarly but more concretely, the “Information-based economy” framework suggests that information and communication technologies are the main drivers of economic growth.

While Godin’s historiographic project of tracing the origins and evolution of 20th century science and technology policy frameworks is already telling, he goes on to consider the nature of these frameworks as a whole, as well as describing how they are generally packaged. He notes the narrative structure of all such frameworks, as well as the importance of metaphor, naming and labeling (which often serves to provide new impetus to old ideas), the generation of statistics, and the inclusion of visual aids. The purpose of each narrative is to provide a heuristic to serve “as a focusing device for how to think about issues, and as a convenient shorthand for how to communicate about them.” These narratives always end in policy recommendations; but remarkably, they change very little despite a feverish rate of publication. At the core of each of these articulated frameworks, indicates Godin, lies the same basic assumption: that more funding for research will lead to more innovation, which will confer untold economic benefits upon the country doing the funding. Thus the new frameworks are not fundamentally new at all; and while quite successful in setting policy agendas, they are as self-serving and reductive as the original Linear model of innovation.


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For a specific case study that complicates the linear model of innovation by demonstrating the complex and multi-directional causation involved in the development of spintronics, see “From Lab to iPod” by Patrick McCray.

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