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Record W4366725925 · doi:10.3138/cjpe.68844

Reconciliation and Energy Democracy

2020· article· en· W4366725925 on OpenAlexvenueaboutno aff
Kimberly A. Scott

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2020
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousDemocracyEquity (law)Energy securityNationalismPolitical scienceSustainable developmentEnergy (signal processing)Inclusion (mineral)Political economyEconomic growthRenewable energySociologyEconomicsPoliticsLawSocial scienceEngineering

Abstract

fetched live from OpenAlex

Abstract: Indigenous clean-energy leaders are moving Canada’s sustainable development agenda along at an impressive rate and are setting the stage for the localization of goods and services. Indigenous communities that do not yet have enough energy security should be the first recipients of green infrastructure investments in order to bolster equity as a tenet of Canadian nationalism. A series of key policy drivers to amplify Indigenous inclusion in the energy transition are offered as well as a number of performance indicators that can determine the extent to which Canada is advancing on reconciliation and energy democracy.

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)0.035
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.866
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0070.010
Scholarly communication0.0070.004
Open science0.0010.012
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.062
GPT teacher head0.265
Teacher spread0.203 · 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 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

Citations11
Published2020
Admission routes2
Has abstractyes

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