Creating a New Path through Creative Capital: Theories and Evidence from the Northern Periphery
Bibliographic record
Abstract
This paper is a review, reflection and synthesis of the last several years of work on creative economy and creative capital in peripheral, remote and northern regions. The focus of this discussion is on the evolving conceptual foundations and supporting evidence from various case studies. Specifically, the paper builds on the new knowledge generated by the Creative Arctic project to expand our understanding of the ‘new path creation’ mechanisms in northern and remote regions though engaging creative capital. The paper summarizes earlier findings and outlines the key ideas that form the foundation of the creative peripheries conceptual framework. Keywords: creative capital; economic development; knowledge economy; periphery; Arctic Créer une nouvelle voie à travers le capital créatif: théories et preuves de la périphérie du nord Résumé Ce document est un article de revue, une réflexion et une synthèse des travaux menés ces dernières années sur l’économie créative et le capital créatif dans les régions périphériques, éloignées et septentrionales. La discussion porte essentiellement sur les fondements conceptuels en évolution et les preuves à l'appui de diverses études de cas. Plus précisément, cet article s’appuie sur les nouvelles connaissances générées par le projet Creative Arctic pour élargir notre compréhension des mécanismes de 'création de nouveaux chemins' dans les régions septentrionales et isolées, tout en engageant un capital créatif. L'article résume les conclusions antérieures et expose les idées clés qui constituent le fondement du cadre conceptuel des périphéries créatives.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".