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Record W2949686194 · doi:10.1177/0263775819855404

Aligning against Indigenous jurisdiction: Worker savings, colonial capital, and the Canada Infrastructure Bank

2019· article· en· W2949686194 on OpenAlexaffabout
Anna Stanley

Bibliographic record

VenueEnvironment and Planning D Society and Space · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsJurisdictionInvestment bankingLeverage (statistics)BusinessIndigenousCapital (architecture)ColonialismFinanceEconomicsPolitical scienceLawGeography

Abstract

fetched live from OpenAlex

This paper considers the significance of the newly conceived Canada Infrastructure Bank in relation to the political economy of settler colonialism in Canada. I argue that the Canada Infrastructure Bank is a fundamentally colonial institution that marshals private capital to reproduce and extend the jurisdictional power of the setter state. The Bank is an arms-length financing institution whose purpose is to leverage private and institutional capital for investment in large scale, nation-building infrastructure, including infrastructure that supports resource extraction in remote and northern Canada. The first section of the paper examines the specific configuration of the Canada Infrastructure Bank. I suggest that the need to attract private investment into certain kinds of infrastructure development must be understood in relation to state struggles to exercise territorial jurisdiction over Indigenous lands and resources. This struggle is reflected in the specific configuration of the Canada Infrastructure Bank. The second part of the paper focuses on some of the implications of pension securitization. The Canada Infrastructure Bank has deliberately been designed to leverage Canadian pension fund capital; I ask what it means to grow settler workers’ savings through investment in privatized, resource development infrastructure.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.163
Teacher spread0.158 · 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 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

Citations29
Published2019
Admission routes2
Has abstractyes

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