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An Investigation into the Link between UK Credit Union Characteristics, Location and their Success

2005· article· en· W2091055709 on OpenAlexaff
Donal McKillop

Bibliographic record

VenueAnnals of Public and Cooperative Economics · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsQueen's University
Fundersnot available
KeywordsCredit historyCredit unionCredit referenceLeagueBusinessFinancial servicesIrishCredit crunchFinanceFinancial systemEconomicsCredit risk

Abstract

fetched live from OpenAlex

Abstract ** : The unique characteristics of credit unions reduces the information asymmetry that is prevalent in credit making decisions, enabling them to provide loans where other financial institutions cannot. This makes them a potential tool in the fight against financial exclusion. Yet, the UK credit union movement is not regarded as being successful, even though there is evidence of much financial exclusion. This study is cross sectional in form, and evaluates characteristics that may contribute to the success of the UK credit union movement at national and regional level, in 2000. The findings are used to consider the impact of recent regulatory changes on the movement. The key findings are that there is a significant relationship between the success of a credit union, its size and the deprivation of the ward from which it sources its members. More specifically, larger credit unions and those located in more affluent wards, are more successful. Affiliation to the Irish League of Credit Unions and having a common bond of occupation, are also found to be contributing factors to credit union success. These results are taken as providing support for the recent changes implemented by the Financial Services Authority (FSA), which is likely to result in the emergence of larger credit unions (through mergers), run by appropriately qualified persons, serving a more mixed‐income membership base. It is, however, noted that the history of the UK movement is one of missed opportunities and only time will tell whether credit unions have the wherewithal to accept current opportunities .

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.063
GPT teacher head0.261
Teacher spread0.198 · 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

Citations8
Published2005
Admission routes1
Has abstractyes

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