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Record W4256285595 · doi:10.17771/pucrio.acad.46550

O CONHECIMENTO FINANCEIRO E SEU IMPACTO DIRETO NO ENDIVIDAMENTO DAS CLASSES DE BAIXA RENDA DO RIO DE JANEIRO

2019· dissertation· pt· W4256285595 on OpenAlexaff
LUIZA CARVALHO NASSER

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsImpactQuest University Canada
Fundersnot available
KeywordsIndex (typography)DebtDescriptive researchSubject (documents)BusinessDescriptive statisticsGeographyPolitical scienceWelfare economicsEconomic growthFinanceEconomicsSociologyLibrary scienceSocial scienceComputer scienceStatisticsMathematics

Abstract

fetched live from OpenAlex

The subject of this study is " The Financial Knowledge and its Direct Impact on the Indebtedness of Lower Income Classes of Rio de Janeiro".The main objective is to identify if the lack of financial education impacts on the level of indebtedness of these classes.The Project was made through a descriptive quantitative research, based on the reviewed literature that led to the creation of a survey that reached 79 responses.The questions approached topics as such as: financial knowledge of the interviewed, their types of debts and possible solutions for their indebtedness.After the analysis, it was possible to conclude that's a correlation between low financial education index and high indebtedness index of the classes studied.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2019
Admission routes1
Has abstractyes

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