The Behavioural Aspects of Financial Literacy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we investigate the contribution of behavioural characteristics to the financial literacy of UAE residents after controlling for demographic factors. Specifically, we test the relationship between financial literacy and behavioural biases such as representativeness, self-serving, overconfidence, loss aversion, and hindsight bias. Using data collected through survey questionnaires, we apply the methodology developed by the Organization of Economic Co-operation and Development (OECD) to compute financial literacy scores. Our overall results show that all behavioural biases except for overconfidence bias are positively related to financial literacy. Furthermore, some biases exhibit a stronger quantitative relationship with financial literacy than others. For example, hindsight bias displays the strongest link to financial literacy, followed by self-serving bias. The weakest but still statistically significant effect is loss aversion bias. Although biases, in general, have negative connotations, behavioural biases appear to be related to higher levels of financial literacy.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it