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The Politics of ‘Economic Inclusion’ in Canada: Past, Present, Prospects

2019· article· en· W2983188316 on OpenAlexaffabout
Geoffrey Hale

Bibliographic record

VenueLondon Journal of Canadian Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsPoliticsDecentralizationVulnerability (computing)FederalismPolitical scienceInclusion (mineral)AccommodationSustainabilityImmigrationPolarization (electrochemistry)Development economicsPolitical economyEconomicsSociology

Abstract

fetched live from OpenAlex

Abstract This article examines Canada’s relative success in restoring ‘economic inclusion’ and ‘inclusive growth’ between the political and economic disruptions of the 1990s and the mid-2010s. Noting competing views of the concept of ‘inclusion’, it explores four major factors which contributed to reducing domestic tensions during this period. These include the intentional accommodation of diverse regional interests through increased decentralization of Canadian federalism, the use of international trade policies to facilitate largely complementary regional economic policies, the restoration of fiscal sustainability in federal economic policies and to varying degrees across provinces, and the cultivation of cross-partisan consensus on immigration policies to avoid the social polarization experienced in other industrial countries. It concludes by noting areas of political vulnerability with the potential to disrupt this consensus.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.810
Threshold uncertainty score0.939

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0260.012
Scholarly communication0.0110.002
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.017
GPT teacher head0.273
Teacher spread0.256 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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