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Record W4229033924 · doi:10.3390/su14031882

The Arctic Highlights Our Failure to Act in a Rapidly Changing World

2022· article· en· W4229033924 on OpenAlexaff
Peter Schlösser, Hajo Eicken, Vera Metcalf, Stephanie Pfirman, M. S. Murray, Clea Edwards

Bibliographic record

VenueSustainability · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFutures contractGlobal warmingArcticClimate changeThe arcticIndigenousAction (physics)Order (exchange)BusinessNatural resource economicsAdaptation (eye)Political scienceEnvironmental scienceEnvironmental planningEnvironmental resource managementEconomicsEcologyPsychologyFinanceOceanography

Abstract

fetched live from OpenAlex

In this perspective on the future of the Arctic, we explore actions taken to mitigate warming and adapt to change since the Paris agreement on the temperature threshold that should not be exceeded in order to avoid dangerous interference with the climate system. Although 5 years may seem too short a time for implementation of major interventions, it actually is a considerable time span given the urgency at which we must act if we want to avoid crossing the 1.5 to <2 °C global warming threshold. Actions required include co-production of research exploring possible futures; supporting Indigenous rights holders’ and stakeholders’ discourse on desired futures; monitoring Arctic change; funding strategic, regional adaptation; and, deep decarbonization through transformation of the energy system coupled with negative carbon emissions. We are now in the decisive decade concerning the future we leave behind for the next generations. The Arctic’s future depends on global action, and in turn, the Arctic plays a critical role in the global future.

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)0.005
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0140.018
Scholarly communication0.0110.006
Open science0.0010.006
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.314
Teacher spread0.302 · 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 designNot applicable
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

Citations14
Published2022
Admission routes1
Has abstractyes

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