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Record W4286282552 · doi:10.14430/arctic75055

Empowering Churchill: Exploring Energy Security in Northern Manitoba

2022· article· en· W4286282552 on OpenAlexafffundvenueabout
Michael Kvern, Patricia Fitzpatrick, Lee-Ann Fishback

Bibliographic record

VenueARCTIC · 2022
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsChurchill Northern Studies CentreUniversity of Winnipeg
FundersUniversity of Winnipeg
KeywordsContext (archaeology)Agency (philosophy)Energy securityPer capitaElectricityEnergy consumptionConsumption (sociology)Energy (signal processing)Renewable energyEnvironmental resource managementSociologyGeographyEnvironmental scienceEngineeringArchaeologySocial science

Abstract

fetched live from OpenAlex

To those living in Churchill, Manitoba, having power means much more than being able to turn on the lights. Using Churchill as a case study, we examine how local context can improve the suitability of energy security definitions for communities in northern Canada. Churchill is an isolated northern municipality with no road access but is connected to the electrical grid. Energy consumption data were collected from utility providers and organized into a community energy profile. Semi-structured interviews (n = 23) and a community workshop (n = 12) identified challenges, opportunities, and a vision for Churchill’s energy system. High per capita energy consumption, especially of transportation (jet fuel) and heat (electricity and propane) sources dominate Churchill’s energy profile. The reliance on air travel and need for heating are realities that define energy systems in the North. Participants expressed desire for increased use of renewables and improved energy efficiency. Churchill is reliant on external sources of power and there is a need for agency and local decision making. Jurisdictional realities and the community’s desire for consideration of local context mean energy security definitions should take a regional approach. Recognizing these findings, we propose a new definition of energy security that fits the circumstances and desires of Churchill and the North.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.401

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0280.007
Scholarly communication0.0040.001
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.242
Teacher spread0.218 · 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 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

Citations6
Published2022
Admission routes4
Has abstractyes

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