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Record W3191386178 · doi:10.14430/arctic74869

Arctic Connectivity: A Frugal Approach to Infrastructural Development

2022· article· en· W3191386178 on OpenAlexvenueno aff
Mette Simonsen Abildgaard, Carina Ren, Israel Leyva-Mayorga, Čedomir Stefanović, Beatriz Soret, Petar Popovski

Bibliographic record

VenueARCTIC · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticThe arcticHuman settlementBusinessEnvironmental resource managementComputer scienceGeographyEnvironmental scienceOceanographyGeology

Abstract

fetched live from OpenAlex

As the Arctic is heating up, so are efforts to strengthen connectivity within the region, enhance the connections from remote settlements to the global networks of trade, and increase sociality. With global interest in the Arctic on the rise, it becomes increasingly relevant to ensure that investments in Arctic infrastructure actually serve the people of the Arctic, while promoting industrial and commercial innovation in the region through widespread access to broadband and Internet of things (IoT) services. This challenge calls for interdisciplinary research strategies that are able to connect and integrate technological and societal approaches, which are commonly applied in isolation from one another. In this article, we propose an interdisciplinary collaborative research agenda for Arctic connectivity. Drawing on examples from Greenland, we stress the need for localized knowledge to design valuable and cost-effective connectivity solutions that cover the needs for everyday life and may also provide a new set of collaborative connectivity tools for innovation at an international level. Such solutions, termed “frugal connectivity,” are vital for the development of connected Arctic communities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.030
GPT teacher head0.290
Teacher spread0.261 · 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.

Study designQualitative
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
Published2022
Admission routes1
Has abstractyes

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