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Record W2055751850 · doi:10.2304/csee.2012.11.3.163

Financial Literacy Education for Citizens: What Kind of Responsibility, Equality and Engagement?

2012· article· en· W2055751850 on OpenAlexaff
Chris Arthur

Bibliographic record

VenueCitizenship Social and Economics Education · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsYork University
Fundersnot available
KeywordsFinancial literacyCritical literacyCivic engagementDisengagement theoryDemocracyLiteracyMoral responsibilityPoliticsPublic relationsSociologyPolitical scienceFinanceEconomicsPedagogyLaw

Abstract

fetched live from OpenAlex

Financial literacy education is often assumed to be a form of technical and/or hermeneutic training that assists citizens as well as consumers make responsible financial decisions. As a form of civic literacy education, financial literacy education is often framed as promoting civic responsibility, equality and engagement. This article calls into question the seemingly common-sense construction of financial literacy as personal money management for citizens and consumers and charges that many of the dominant financial literacy education initiatives support civic irresponsibility, inequality and disengagement. From a perspective informed by critical theory and pedagogy, the first three sections of this article analyse the character of the civic responsibility, equality and political engagement promoted in the dominant financial literacy education literature while presenting critical alternatives for each. The analysis in these sections supports the claim made in the fourth and final section of this article that a critical, emancipatory civic financial literacy is needed for a responsible, engaged citizenry who can extend and protect more robust conceptions of freedom and democracy.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.957

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 head0.076
GPT teacher head0.310
Teacher spread0.234 · 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 designTheoretical or conceptual
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

Citations43
Published2012
Admission routes1
Has abstractyes

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