Learning and Innovation: Implications for Regional Policy. an Introduction
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
Since the late 1990s, learning and innovation have captured the attention of an increasing number of researchers and policymakers: this interest, fuelled in part by the advent of the 'knowledge economy', and the changing ways in which information is disseminated and shared, has led to some pragmatic questions. One of these concerns the policy implications of learning and innovation for regional development. Indeed, from Michigan (CSLR 2001) to South East England (SEEDA 2001) -- via Copenhagen (Maskell and Tornquist 1999) and Finland (LUT 2001) -- there has been a proliferation of policy initiatives aiming to stimulate development through the encouragement of learning and innovation. These concepts -- whilst attractive and unobjectionable -- are neither clear nor readily operational, and their relationship with space is still a matter of debate (Malecki and Oinas 1999; Echeverri-Carroll and Brennan 1999; Sivitanidou 1999). Furthermore, although there is a good deal of high quality descriptive literature which puts forward the characteristics of individual learning regions (for example, Braczyk 1998; Acs et al 2000; Boekema et al 2000) there have so far been fewer publications that attempt to draw out general characteristics and definitions, which alone could justify widespread policy intervention. In this special edition of the Canadian Journal of Regional Science, we attempt to extend the empirical field and advance reflection on the spatial dimensions of learning and innovation. We have gathered six articles by leading researchers from across Europe and Canada: without pretending to have reached the sought after conceptual clarity, the collection grapples with the link between learning, innovation and regional policy. The principal issues addressed are: * how does recent thinking on learning and innovation affect regional economies? * do regions play a role in the learning and innovation process? * are there any lessons to be learned in terms of regional development policy? Learning, Innovation and Regional Policy It is clear from the articles which follow that the link between learning, innovation and regional policy can be interpreted in two distinct ways. On the one hand, Cooke and Lamari et al examine innovation at the firm level, and their articles, from very different perspectives, suggest means whereby policymakers can enhance innovative behaviour in the firm. In this sense, an innovative region is one in which establishments and firms are at the forefront of technique and procedure. On the other hand, Maillat and Kebir and Lajendijk examine innovation at the policy level. For them, an innovative region is one in which innovative policies and institutions emerge in response to the changing national and global environment. These two interpretations are not unconnected: Cooke and Lamari et al suggest new policy responses to encourage innovative behaviour at the firm level, whereas Maillat and Kebir and Lajendijk recognise that a possible aim of innovative regional policy is to enhance firm level innovation. Isakse n and Guillaume both integrate the two approaches and directly consider innovative policy responses that encourage innovative behaviour in firms. Cooke, in the first article of this volume, provides an introduction to the concept of regional innovation systems. He does so by first describing a variety of territorial policy approaches, drawn from France and Japan, which attempted to stimulate technopoles and science parks in the 1970s and 1980s. In so doing, the variety of physical and institutional arrangements which have been experimented becomes evident: Sophia Antipolis -- which is basically a large business park between Cannes and Nice in France -- is a technopole, as is Sendai, a Japanese city of 800,000 people. The question of the geographic scale at which such regional policies operate is a key one which emerges from Cooke's analysis. …
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| 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 it