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Record W4361002128 · doi:10.18357/ijcyfs141202321286

MISSING THE MARK: THE IMPORTANCE OF FINANCIAL ANXIETY IN FINANCIAL SKILLS TRAINING FOR FOSTER YOUTH

2023· article· en· W4361002128 on OpenAlexaffvenueabout
Amanda Keller

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsFinancial literacyIntervention (counseling)PovertyEmpowermentPositive Youth DevelopmentWelfareFinanceFoster careAnxietyPsychologyBusinessPublic relationsEconomic growthPolitical scienceEconomicsNursingMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

It is well established that many former Canadian foster youth struggle with financial issues after aging out of care. Much of the financially focused intervention literature speaks to financial literacy training within independent living programming (ILP) or financial empowerment within individual development accounts (IDAs). These important programs offer educational modules to address financial skills or increase youth access to savings. Yet they are not sufficient, as neither addresses the emotional side of personal financial decision-making. Growing up in poverty can create emotional challenges related to money, such as financial anxiety. Financial anxiety affects quality of life in complex ways. Using three clinical composite profiles of youth aging out of the youth protection system in Quebec, this paper highlights some of the complex challenges faced by foster care alumni in dealing with economic insecurities. It is our proposition that we must be more mindful of current and former foster youth’s financial well-being and adapt financial literacy training accordingly. Further, these programs must be assessed for short- and long-term efficacy. Neglecting to measure and address financial anxiety for foster youth and alumni of care risks setting them up for preventable hardships and failures. This paper thus proposes that Canadian child welfare organizations and research teams must further develop this area of inquiry and intervention.

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)0.001
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 score0.027
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.040
GPT teacher head0.279
Teacher spread0.238 · 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

Citations6
Published2023
Admission routes3
Has abstractyes

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