Students Perception About Digital Financial Services
Bibliographic record
Abstract
The purpose of this research is to determine how the students from a Mexican university perceive the different digital financial services. For the study, the Durai and Stella (2019) test was used, which is made up of twelve indicators in a Likert format to assess the perception of digital services, based on their convenience, adaptability, affordability, security, user-friendliness, trailing fee, accurate timing, online monthly statement, quick financial decision making, interbank account accessibility and internet connectivity. The main findings point to the satisfaction that respondents feel towards digital financial services in the five dimensions that were studied: Internet Banking, Mobile Banking, Mobile Wallet, Credit Cards and Debit Cards. Student’s perception was extremely satisfactory towards Debit Card services, especially on the indicators of adaptability, affordability, security, user-friendliness, accurate timing, online monthly statement and portability. In addition, the Mobile Banking services had a positive impact on the Interbank account accessibility and Internet Connectivity. This could be explained by the way these current generations of young millennials easily handle technological use.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".