Financial Behaviors of Female Teachers in Malaysia
Bibliographic record
Abstract
This paper aims to identify the pattern of financial behavior among female teachers in Bandar Baru Bangi, Selangor. A total of 325 female teachers was involved in the study. Questionnaires were used in the survey to collect data. Data on questions relating to socioeconomic background, financial knowledge and financial behavior were gathered. The financial behavior pattern was formulated using the 5-Likert scale and financial knowledge with the choice of either ‘right’ or ‘wrong’ answer. The analysis showed four dimensions that were interrelated on the assessment measurement of financial behavior: i) planning, ii) cash flow management, iii) saving and iv) usage of credit card. Descriptive analysis includes t-test and ANOVA were used to analyze the differences between the mean score of financial behavior across the factors such as age, level of education, monthly income and financial knowledge level. The findings showed the respondents had a substantial mean score in the four dimensions of financial behavior described above. The highest mean score was on the dimension of cash flow management which involve activities of paying bills and other expenses by installments. The findings also showed respondents aged more than 45 years old had good financial behavior in term of saving. In another word, as they grew older they cultivate better saving habit. The findings also showed that the respondents with the good financial behavior were among those who were good in saving their income. Further study is suggested to identify factors that influence the financial behavior among teachers. The financial behavior can describe the financial well-being of an individual or group which has an impact on the individual productivity level.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".