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Record W7101437164 · doi:10.5281/zenodo.17454264

Strategies for circular economy in the Nordics: a comparative analysis of directionality

2024· article· W7101437164 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Language
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsDirectionalityPoliticsSustainabilityParadigm shiftTransition (genetics)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.007
Science and technology studies0.0030.007
Scholarly communication0.0110.006
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.076
GPT teacher head0.321
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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