Strategies for circular economy in the Nordics: a comparative analysis of directionality
Bibliographic record
Abstract
In this paper we mobilize sustainability transitions literature to explore directionality for circulareconomy (CE) transitions, by drawing on and adapting a framework for analysing roadmaps to empiricallyinvestigate CE strategies. Specifically, this paper explores circular economy CE strategy documentsin the Nordics, the commonalities and differences between them and to what extent theyprovide directionality for CE transitions. Through a systematic document analysis of 39 CE strategydocuments, we find that the strategy documents are vague and lack clear political visions. As such,we argue that the documents fail to provide clear directionality for CE transitions and question theirusefulness. Additionally, the paper demonstrates how CE strategy documents can contribute to promotingthe development of industries that couple to national ambitions for the development of new,green industries.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".