Bibliographic record
Abstract
The research is an experimental exploration of the domestic income and expenditure in district Bagh AJ&K (Pakistan). The study utilized primary data of March 2020 gathered through a well-developed cum comprehensive questionnaire. It comprised a sample of 400 households selected through random sampling technique. The outcome was analyzed by applying “ordinary least square” (OLS) “regression model” and ANOVA test. Results of the study showed that relationship between income of household and domestic consumption is positive and significant. It means that the increase in the domestic income also increases their consumption. This result also contented the Keynesian theory on consumption. There is no significant impact occurred to take the gender of household and consumption. So, this study omits this variable from the model. There was a positive and substantial relationship existed between household age and domestic consumption. Households’ education and domestic consumption also had a constructive and meaningful relation. It means that educated people spend more as compare to less educated. There was a negative and noteworthy relationship existed between family structure and household consumption. Family size and household consumption had been also completely correlated. Nonetheless, the research determined that both economic factors and demographic features affect household consumption pattern in district Bahg AJ&K. Policy makers should formulate policies designed to increase the income level of employees for enhancing their buying power, decreasing their deficit and to increase their saving which would definitely ensure a sophisticated living standard of the study area.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.973 | 0.973 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".