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Record W4392815881 · doi:10.29173/jaed318

Alternative Approaches To Hydro Compensation And Agreements With First Nations: Manitoba and Quebec

2012· article· en· W4392815881 on OpenAlexafffundabout
John Loxley

Bibliographic record

VenueJournal of Aboriginal Economic Development · 2012
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of CanadaManitoba Hydro
KeywordsNegotiationHuman settlementEquity (law)PoliticsRevenueIntergenerational equityCompensation (psychology)Settlement (finance)Political scienceBusinessEconomicsLawGeographyFinanceSustainability

Abstract

fetched live from OpenAlex

This paper outlines the workings of two quite different contemporary approaches to settlements and agreements with First Nations by hydro companies and governments involved in hydro dam construction. The first is the equity approach used by Manitoba Hydro in negotiations with the Nisichawayasikh Cree Nation (NCN) in which the First nation is effectively offered joint ownership of the dam and a share in future income streams and in employment and construction benefits. The second approach is that by the James Bay Cree of northern Quebec who eschew dam ownership, instead negotiating an annual share in revenues generated by hydro, forestry and mining. Both approaches constitute major improvements over disastrous earlier approaches which can be summarized as 'flood now and talk later', but they carry quite different economic. Political and governmental terms as well as quite different potential benefits and risks. This paper examines the background behind each deal and the way in which they operate. It concludes by arguing that each deal was conditioned by circumstances and history. There is, however, clear merit in Aboriginal People seeking to secure maximum control over and benefit from all sources of economic development on their traditional lands.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.111
Threshold uncertainty score0.807

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0150.006
Scholarly communication0.0070.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.000

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 head0.027
GPT teacher head0.210
Teacher spread0.184 · 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 designObservational
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
Published2012
Admission routes3
Has abstractyes

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