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Record W4251223288 · doi:10.6027/tn2014-568

Arctic Social Indicators

2015· report· en· W4251223288 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticThe arcticGeographyEnvironmental scienceOceanographyGeology

Abstract

fetched live from OpenAlex

Arctic Social Indicators II (ASI-II) is a follow-up activity to ASI-I (2010) and the first Arctic Human Development Report (AHDR, 2004). The objective of ASI (2010) was to develop a small set of Arctic specific social indicators that as a collective would help facilitate the tracking and monitoring of change in human development in the Arctic. ASI indicators were developed for six domains that are considered prominent aspects of human development in the Arctic by residents in the Arctic: Health and Population; Material Wellbeing; Education; Cultural Wellbeing; Contact with Nature; and Fate Control. The objective of the present volume of ASI is to present and discuss the findings of the work on measuring the set of recommended ASI indicators; to conduct a series of regional case studies to illustrate and test the strength and applicability of these indicators; to identify and describe data challenges for the Arctic region specifically in relation to these Arctic specific indicators and to draw conclusions about the ability of ASI to track changes in human development; and to formulate policy relevant conclusions for the long-term monitoring of Arctic human development. The core content of ASI-II is a set of five carefully selected case studies, which form the basis for drawing conclusions about the applicability of the ASI indicators and for formulating policy relevant conclusions. Case studies are performed for Sakha Republic (Yakutia); the West-Nordic Region; Northwest Territories; Inuit Regions of Alaska; and the Inuit World, with the Survey of Living Conditions in the Arctic (SLiCA) used to augment ASI. Findings on the state and changes in Arctic human development and wellbeing are presented. Based on our analysis and conclusions from the five case studies the framework for an ASI monitoring system is introduced. We argue that the long-term monitoring of human development in the Arctic would be greatly facilitated by the regular and frequent collection and reporting of relevant data, including those required for the proposed small set of ASI indicators.

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)0.010
metaresearch head score (Gemma)0.035
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: none
Teacher disagreement score0.125
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0160.022
Science and technology studies0.0030.001
Scholarly communication0.0060.003
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0670.038

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 head0.111
GPT teacher head0.418
Teacher spread0.307 · 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

Citations20
Published2015
Admission routes1
Has abstractyes

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Same topicArctic and Russian Policy StudiesFrench-language works237,207