Does geographical clustering pay? Analysis of the Norwegian salted and dried cod industry
Bibliographic record
Abstract
The structure of the Norwegian salted and dried cod industry is manifold, with differences both regarding plant size and type of organisation. The cluster of manufacturers and exporters of this industry in the North-Western region of Norway contributes considerably to total exports, and the main location for these firms is the Ålesund region. Ålesund is also the most important Norwegian town for exports of fish and fish products in general. It is well known from literature that geographical clustering of firms may induce self-reinforced growth effects. In an increasingly more competitive global environment, with stronger competition from producers and exporters in countries like e.g. Iceland, Canada, Russia, Portugal and China, it will be important to preserve and even strengthen such a cluster. In order to recommend adequate policy to support the development of this cluster one must recognize the mechanisms that create innovation and value added. To reveal possible localized external returns to scale in the regional salted and dried cod industry, a panel of firms is analysed by estimating a production function including both internal production factors and external economy variables. One important source of positive cluster-effects can be associated with immaterial capital related to connections between different actors within the industry. Preliminary results show that there is a significant localized external effect in this cluster, implying that geographical clustering in the central Ålesund region will induce more value added than otherwise.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".