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Record W2585589725 · doi:10.22230/cjnser.2016v7n2a236

Is There a Credit Union Difference? Comparing Canadian Credit Union and Bank Branch Locations

2017· article· en· W2585589725 on OpenAlexaffvenueabout
John Maiorano, Laurie Mook, Jack Quarter

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCredit unionQuarter (Canadian coin)PopulationCredit historyDemographic economicsEthnic groupBank creditCredit card interestDimension (graph theory)EconomicsGeographyFinancial systemCredit riskCredit referencePolitical scienceFinanceDemographySociology

Abstract

fetched live from OpenAlex

This study of credit union and bank branch locations and neighbourhoods in Canada seeks to discover if there is a distinct credit union niche. The study builds on an earlier paper of credit unions and banks in the US which found that credit unions in Wisconsin, Arizona and New Hampshire were more likely to be located in lower-income areas than bank branches (Mook, Maiorano & Quarter, 2015). In Canada, we find that credit union branches are over-represented in rural areas, and under-represented in large population centres relative to bank branches. Additionally, credit unions are overrepresented in middle income areas and underrepresented in high income areas compared to bank branches both at the national level and in all provinces where differences are statistically significant. Another significant finding is that while both credit unions and banks cater to marginalized communities, the type of marginalized communities they cater to distinguishes them. Making use of the Canadian Marginalization Index, we find credit union branches in Canada to be overrepresented in communities marginalized along the dimensions of Material Deprivation and Dependency, while bank branches are overrepresented in communities marginalized along the dimension of Residential Instability and Ethnic Concentration.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.369
Teacher spread0.217 · 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.

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

Citations6
Published2017
Admission routes3
Has abstractyes

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Same venueCanadian journal of nonprofit and social economy researchSame topicUrban, Neighborhood, and Segregation StudiesFrench-language works237,207