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Record W4379232756 · doi:10.1080/1088937x.2023.2210315

Model Arctic Council for sustainable development

2023· article· en· W4379232756 on OpenAlexaff
Anthony Speca

Bibliographic record

VenuePolar Geography · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsTrent University
Fundersnot available
KeywordsArcticNegotiationSustainable developmentExperiential learningValue (mathematics)Education for sustainable developmentAction (physics)SociologyPolitical sciencePedagogyComputer scienceSocial scienceLawEcology

Abstract

fetched live from OpenAlex

I argue that Model Arctic Council (MAC) has a role to play in Arctic sustainable development. Like the better-known Model United Nations (MUN), MAC is a form of simulation pedagogy, an experiential learning process in which secondary-school pupils or university students comprehend the nature and importance of complex issues such as sustainable development by imagining themselves as diplomats trying to negotiate a common approach to them. After demonstrating the educational value of diplomatic simulations in general, I introduce MUN as its most popular form, and I assess a case-study of a global MUN program designed to advance knowledge and action among youth in respect of the UN Sustainable Development Goals. This case-study, taken together with the structure, subject-matter and educational value of MAC itself, strongly suggests that MAC can be used to advance knowledge and action among both Arctic and non-Arctic youth in respect of Arctic sustainable development, including understanding how the notion of sustainable development is both contested in general and contextualized in the Arctic. Combining this analysis with professional experience, I offer practical recommendations to educators about the effective design and use of MAC and other simulation pedagogies.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.077
GPT teacher head0.319
Teacher spread0.242 · 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
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

Citations5
Published2023
Admission routes1
Has abstractyes

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