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Record W2072192645 · doi:10.1080/20430795.2013.776259

Lessons in operationalizing social finance: the case of Vancouver City Savings Credit Union

2013· article· en· W2072192645 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Sustainable Finance & Investment · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsUniversity of Waterloo
FundersScience Foundation Ireland
KeywordsCredit unionOperationalizationFinanceAllianceBusinessFinancial servicesAsset (computer security)PortfolioEuropean unionFinancial systemEconomic policyPolitical science

Abstract

fetched live from OpenAlex

With $16.2 billion of assets the Vancouver City Savings Credit Union (Vancity) has the largest asset base of any member of the Global Alliance on Banking and Values, a global association of ethical banks, and also has the largest asset base of Canada's credit unions. This article analyses the social financing Vancity conducts and the disclosure of the social impact of the products and services they offer. The results suggest that they are on the path to realizing a 100% social finance portfolio but that they have not arrived there yet. In particular, their personal retail products and services still offer room for improvement. Furthermore, their reporting lacks an indicator based on comparative figures that would allow stakeholders to compare the impact of Vancity's products and services with those of other financial institutions.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.246
Teacher spread0.221 · 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