Aprimorando a inclusão financeira: rumo a um quadro teórico de educação financeira crítica
Bibliographic record
Abstract
Empirical research suggests that financial inclusion initiatives – such as facilitating access to financial resources or providing microcredit – are alone not enough to lower socioeconomic disparities. In this article, we adopt a critical stance as a guide for our empirical investigation. Our aim is to propose a financial education framework, tailored to low-income micro-entrepreneurs, that embraces new information and communication technologies (ICTs) and seeks to improve financial inclusion and social emancipation. This empirical study was conducted in an Amazonian municipality in Brazil where recent access to ICTs has brought about important and varied socioeconomic changes. Results show that ICT-supported and tailored critical financial education can play a dual role: on the one hand, access to financial education might decrease the effects of generative mechanisms on global/local tensions, triggered by standardized ICT applications; on the other hand, such access might increase financial inclusion and social transformation through the integration of guiding principles into financial education programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".