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Record W3100985018 · doi:10.3390/su12229476

Promoting LNG as A Marine Fuel in Norway: Reflections on the Role of Global Regulations on Local Transition Niches

2020· article· en· W3100985018 on OpenAlexaff
Sofiane Laribi, Emmanuel Guy

Bibliographic record

VenueSustainability · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsSustainabilityProcess (computing)Scale (ratio)NicheFossil fuelTransition (genetics)BusinessEcological nicheIndustrial organizationLiquefied natural gasPerspective (graphical)Economic geographyEnvironmental resource managementEconomic systemEnvironmental economicsEconomicsEcologyGeographyNatural gasComputer science

Abstract

fetched live from OpenAlex

Contemporary societies are marked by constant tensions between the notion to improve sustainability and the reluctance to engage in uncertain changes. In any sector, the transition is a delicate and complex process that involves many actors, organizations, and institutions. Niche analysis approaches such as the multilevel perspective model (MLP) explain how such a process grows from innovation within a very restricted field to its generalized application on a global scale. Shipping is a sector particularly challenged by the transition process away from heavy fuel oil towards more environment-friendly alternatives such as liquefied natural gas (LNG) or even non-fossil alternatives. Within this industry, Norway stands as an early adopter and leader of the emerging transition. Drawing from a wide discussion of the treatment of scale in transition literature and from this national case study, we propose that the transition process can emerge not only from a local niche perspective, as widely documented in the literature, but can also be driven by changes at a much larger scale and initiated by new international regulations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.340
Teacher spread0.317 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations15
Published2020
Admission routes1
Has abstractyes

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