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Record W2111627076 · doi:10.1177/0741713609358449

Are Low-Income Canadians Financially Literate? Placing Financial Literacy in the Context of Personal and Structural Constraints

2010· article· en· W2111627076 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

VenueAdult Education Quarterly · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsCanadian Mennonite University
Fundersnot available
KeywordsFinancial literacySocioeconomic statusContext (archaeology)Government (linguistics)LiteracyBusinessLow incomeFinancial servicesEconomicsEconomic growthFinanceSociologyDemographic economicsGeographyPopulation

Abstract

fetched live from OpenAlex

This article argues that financial literacy varies across socioeconomic groups and their neighborhoods, in part because of the adult learning that occurs within a local context. The study begins by explaining that financial literacy needs vary across socioeconomic groups and that there are important structural factors affecting the financial well-being of low-income people. Drawing on data from qualitative field research undertaken in three Canadian inner cities, it then moves to examine low-income respondents’ financial literacy. The results show that many low-income respondents evidenced financial literacy in that many learned to cope with strict budgets, used diversified activities to raise their income, constrained their credit, and were reasonably knowledgeable about relevant government programs and banking services. Where particular constraints were noted in financial literacy, they related to detailed knowledge about institutional policies and attitudes about deeper financial and life goals.

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)0.000
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 score0.070
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.004
GPT teacher head0.223
Teacher spread0.219 · 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