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Strategies of universities in northern Europe and North America in the field of sustainable development

2024· article· en· W4404652155 on OpenAlexaboutno aff
V. M. Savvinov, L. A. Neustroev

Bibliographic record

VenueVestnik of North-Eastern Federal University Pedagogics Psychology Philosophy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsnot available
Fundersnot available
KeywordsField (mathematics)Sustainable developmentGeographyPolitical scienceRegional science

Abstract

fetched live from OpenAlex

The article presents an analysis of the strategies of universities in Nordic countries and North America to achieve the Sustainable Development Goals. It demonstrates that the sustainable development of northern territories holds one of the first places on the scientific and technical agenda of the leading countries of world science. The article discusses the methods and practices used to implement the concept of sustainable development and the principles of equality and inclusivity. It also discusses measures taken to preserve the languages and cultures of the indigenous peoples in the North, as well as efforts to promote diversity and engagement. It is shown that a significant part of the long-term objectives defined in the strategies of universities in Northern Europe and North America is aimed at increasing their contribution to the sustainable development of regions, a climate-neutral society, reducing inequality and the development of indigenous peoples. Based on the case studies of universities in Finland, Sweden, Norway, Greenland, Canada and the USA, recommendations are given for Arctic universities in Russia on the development and adjustment of ESG strategies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.038
GPT teacher head0.340
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 teacher head, 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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