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Record W2884626595 · doi:10.4324/9781351171243

Society, Environment and Human Security in the Arctic Barents Region

2018· book· en· W2884626595 on OpenAlexfundno aff
Kamrul Hossain, Dorothée Cambou

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
FundersLapin YliopistoÅbo AkademiNordForskForeign Affairs and International Trade CanadaUniversity of TorontoHelsingin YliopistoSylff AssociationInternational Institute for Applied Systems AnalysisUniversity of Cambridge
KeywordsHuman securityArcticThe arcticPolitical scienceOceanographyGeologyLaw

Abstract

fetched live from OpenAlex

The Arctic-Barents Region is facing numerous pressures from a variety of sources, including the effect of environmental changes and extractive industrial developments. The threats arising out of these pressures result in human security challenges.This book analyses the formation, and promotion, of societal security within the context of the Arctic-Barents Region. It applies the human security framework, which has increasingly gained currency at the UN level since 1994 (UNDP), as a tool to provide answers to many questions that face the Barents population today. The study explores human security dimensions such as environmental security, economic security, health, food, water, energy, communities, political security and digital security in order to assess the current challenges that the Barents population experiences today or may encounter in the future. In doing so, the book develops a comprehensive analysis of vulnerabilities, challenges and needs in the Barents Region and provides recommendations for new strategies to tackle insecurity and improve the wellbeing of both indigenous and local communities. This book will be a valuable tool for academics, policy-makers and students interested in environmental and human security, sustainable development, environmental studies and the Arctic and Barents Region in particular.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.233
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.035
GPT teacher head0.304
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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