Liability or opportunity? Reconceptualizing the periphery and its role in innovation
Bibliographic record
Abstract
Abstract The continued emphasis on innovation in urban and clustered settings has led many geographers to conceive peripheries as laggard and non-innovative. After reconstructing discussions of the periphery in the context of the geography of firm-level innovation, we argue that normative connotations should be stripped away, and that ‘periphery’ and ‘center’ are better understood as positions in a field. We draw upon concepts current in network theory and propose a relational definition of periphery as a distant, dispersed and disconnected position relative to a core within a field. A key distinction is made between the position of an actor in geographical space (location) and the position of an actor in a social network of relations. Combining geographic and network dimensions of an actor’s position, our aim in this article is to propose a dual core-periphery framework which provides the vocabulary and concepts to empirically scrutinize the role of periphery in innovation processes. Although we focus on the geography of innovation, this framework can be applied more broadly to discussions of peripherality.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.043 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".