Relationship between saving and investment pattern and orientation towards finance among working women in the universities of Saudi Arabia
Bibliographic record
Abstract
The main objective of the study was to find out the relationship between saving and investment pattern and orientation towards finance among the working women at the universities of Saudi Arabia. Orientation towards finance (ORTOFIN) is one's attitude towards effectively managing financial activities. This attitude is backed by individual behavior toward financial management. ORTOFIN scale was made as a construct to measure the behavioral dispositions of individuals that are connected to their behavior patterns towards finance and orientations. The data was collected using the ORTOFIN scale which was constructed and used in the European population as well as validated using standard procedures into the Asian population. The present study concentrates on the working women at the Universities of Saudi Arabia. The data collected from 192 women employees of different Universities in Saudi Arabia. This study states there is a significant positive relationship among the saving and investment pattern and orientation towards finance among the working women at the universities of Saudi Arabia. The finding of the study revealed Financial Management Behavior act as a major contributor to the orientation towards finance and the factor of personnel planning is another significant contributor towards ORTOFIN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".