Government Policies for Promoting Financial and Fiscal Literacy: Evidence from a Questionnaire-Based Study
Bibliographic record
Abstract
This paper aims to assess the level of financial and tax literacy among the resident population in Portugal, as well as to evaluate their perception of existing public measures in this field. Financial literacy is a key pillar for individual development and for making informed economic decisions. Recent data indicate that Portugal lags behind the European average in this area, underscoring the importance of this research. Using a questionnaire applied to a representative sample of the Portuguese population, the data were analysed through statistical methods. The results reveal a reasonable level of knowledge in areas such as budgeting and saving, but also significant shortcomings in the tax domain. In a global context marked by economic, political, and geopolitical instability, financial literacy stands out as a strategic skill essential for both individual and collective resilience. A lack of competence in this area is linked to poor financial decisions, over-indebtedness, and economic exclusion. The findings underline the need for a more systematic and structured approach to financial literacy in Portugal. This study offers practical recommendations designed to promote a more informed, prepared, and financially inclusive population, thereby contributing to the country’s economic sustainability and development.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".