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Record W2509082021 · doi:10.3138/jcs.49.3.191

Management of Distributive Conflicts Impeding Expansion of Interprovincial Hydroelectricity Transmission

2015· article· en· W2509082021 on OpenAlexvenueaboutno aff
Douglas MacDonald, Matthew Lesch

Bibliographic record

VenueJournal of Canadian Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDistributive propertyContext (archaeology)Distribution (mathematics)Government (linguistics)HydroelectricityEconomicsPolitical sciencePublic economicsGeographyEcology

Abstract

fetched live from OpenAlex

Conflicts over distributive effects are a perennial feature of policy-making. The purpose of this essay is to investigate how such distributive conflicts unfold in the context of interprovincial hydroelectricity transmission. Through analysis of two Eastern Canada agreements on interprovincial transmission, plus a related third case, the authors present three major findings. First, the relative distribution of associated impacts—material, non-material, and environmental—is important and often presents a significant barrier to interprovincial agreement. Second, the authors find the distribution of non-material impacts, related to both perceptions of fairness and provincial identity, is perhaps as significant as distribution of financial cost and benefit. Third, the authors find that weak intergovernmental institutions in Canada and ad hoc interventions by the federal government further compound the challenge. The authors argue that future efforts to expand hydro transmission across provincial boundaries are needed to address climate change, but to succeed they must address the challenge of all three types of distributive effects and be supported by consistent federal government leadership.

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 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 score0.794
Threshold uncertainty score0.947

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 studies0.0000.000
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 head0.058
GPT teacher head0.333
Teacher spread0.275 · 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

Citations3
Published2015
Admission routes2
Has abstractyes

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