Regional economic development: institutions, innovation and policy
Bibliographic record
Abstract
The spatial dynamics of regional innovation cannot be explained by the locational decisions of firms and workers alone. Globalization continues to put primacy on the relationship between public policy and the economic competitiveness of regions. Policy makers across the Organisation for Economic Co-operation and Development (OECD) countries are preoccupied with ways to encourage knowledge-intensive regional growth, not just in places where it is already well established but also in those struggling for reinvention. Largely resourced by public policy, a complex mix of formal and informal institutions shapes the context in which much economic activity occurs. This chapter brings institutions ‘in’ to the discussion of regional economic development, drawing analytical attention to the multi-level nature of economic innovation and how the interplay among different levels of government and multiple public and private sector actors shapes regional development trajectories. The three intersecting themes of governance, scale and agency provide an analytical framework for examining the ways in which ‘top-down’ multi-level institutional structures and ‘bottom-up’ associational governance dynamics enable and constrain regional restructuring and innovation. Following a conceptual overview of the New Regionalism, we offer brief policy illustrations of these ‘ideas in action’, highlighting selected regional innovation programmes underway in the European Union, the United States, and Canada, three jurisdictions long known for government engagement with problems of regional decline and renewal.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".