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Record W2270847923

Changing regional income disparities and fiscal transfers in Canada from 1951 to 1991

2011· article· en· W2270847923 on OpenAlexaboutno aff
Wang Peng-fei

Bibliographic record

VenueGeographical Research · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economic and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGini coefficientEconomicsDemographic economicsInequalityTheil indexDisequilibriumTransfer paymentConvergence (economics)Per capita incomeEconomic inequalityPer capitaDevelopment economicsGeographyEconomic growthDemographyWelfarePopulation
DOInot available

Abstract

fetched live from OpenAlex

In this paper,we analyze regional income disparities and fiscal transfers changes in Canada from 1951 to 1991 based on statistical data and clarify their structure of change.For this purpose,this study describes that the changing inter-provincial differentials of personal income per capita is specified using Gini coefficient,the coefficient of variation and Theil's measure.The results of the survey lead to the following conclusions. The disparities gradually decreased from the early 1950s to late 1960s and dropped sharply in the early 1970s.During the following decade,the disparities tended to decrease significantly from the mid-1970s,and the decrease in disparities became steady in the early 1980s.Based on Theil's measure,the disparities within eastern provinces and between eastern and western regions showed a remarkable reduction.The role of fiscal transfers in the changing regional income inequalities is examined.The expanding disparities within western provinces during the 1980s are responsible for the diverging total disparities.We do not consider that economic growth rate had a significantly negative effect on the divergence of the regional inequalities.These results support disequilibrium and transition perspectives in the sense that an economic boom can increase the relative strength of expansion,and a depression can decrease the effect in Canada.It is true that the convergence of regional inequalities is mainly caused by the expanding fiscal transfers,but this does not mean a sustainable economic growth of low income provinces.This implies that they have increasingly depended upon government transfers in terms of economic well being.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.099
GPT teacher head0.252
Teacher spread0.153 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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