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Record W4403702745

A Regional Perspective on the Canada-US Standards of Living Comparison

2000· article· en· W4403702745 on OpenAlexaffabout
Raynald Létourneau, Martine Lajoie

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsInnovation, Science and Economic Development Canada
Fundersnot available
KeywordsPerspective (graphical)Regional scienceGeographyEconomic geographyComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a comparison of standards of living between Canadian provinces and U.S. states. Most comparisons with the United States focus on the national perspective, while provincial analyses are essentially restricted to the domestic context. This study extends the scope of the exercise to the regional level since, as shown in our previous studies,1 the relative performance of the provinces varies significantly and, therefore, the challenges raised by the greater integration of the North-American market are also likely to differ. The comparison focuses on standards of living with a special emphasis on labour productivity. The paper is divided as follows. First, we present our framework of analysis and discuss issues related to the comparison of productivity and standards of living at the regional level between the two countries. We then move to a discussion of standard of living and productivity. Each of these sections presents a separate analysis of U.S. states and Canadian provinces, and a comparison of both. The paper concludes with a brief review of our main results.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.059
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.016
Science and technology studies0.0050.003
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.207
GPT teacher head0.551
Teacher spread0.343 · 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
Published2000
Admission routes2
Has abstractyes

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