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Record W3027759878

The influence of financial attitude, behaviour and knowledge on financial literacy: a Malaysian perspective / Amira Rosalia Aripin

2019· dissertation· en· W3027759878 on OpenAlexaboutno aff
Amira Rosalia Aripin

Bibliographic record

VenueUiTM Institutional Repositories (Universiti Teknologi MARA) · 2019
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial literacyNonprobability samplingFinanceContext (archaeology)DebtDeveloping countrySample (material)BankruptcySampling framePerspective (graphical)BusinessPsychologyEconomicsSociologyGeographyEconomic growthPopulation
DOInot available

Abstract

fetched live from OpenAlex

Financial Literacy among youths is a global concern worldwide. This includes alarming problems such as the high bankruptcy level among youths and the weaknesses in managing finance among youths such as managing debt, personal finance and savings. The GECD has provided a framework which assess the Financial Attitude, Financial Behaviour and Financial Knowledge to determine the level of Financial Literacy among youths. However, the result will very much vary within countries such as first world countries like UK, Canada, and Germany and third world countries like India, Bangladesh and Vietnam. Thus it is significant to carry out the study in Malaysia. This study has been conducted among 220 youths with purposive sampling method. It uses primary data which is derived from questionnaires that have been distributed to individuals from different field of expertise and working fields. Secondary data are also used to help researcher in getting a clearer picture of the situation on a global perspective. The definition of youths in the Malaysian context refers to those 30 years old and below. The time frame of conducting the study is within the year 2019 and it is not time significant. The result has shown that between the variables 'Financial Knowledge' is the most significant in determining the level of financial literacy among youths in Malaysia. However, there are some limitations in the study such as the sample size, the scope of variable used and medium to collect the data.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.238
Teacher spread0.231 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueUiTM Institutional Repositories (Universiti Teknologi MARA)Same topicFinancial Literacy, Pension, Retirement AnalysisFrench-language works237,207