Agricultural Sub-Sectors Performance: An Analysis of Sector-Wise Share in Agriculture GDP of Pakistan
Why this work is in the frame
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Bibliographic record
Abstract
This study focused on the agricultural sub-sectors performance: an analysis of sector-wise share in agriculture GDP in Pakistan by using secondary data from 1998 to 2015. Ordinary Least Square (OLS); an econometric method was applied to estimate the model parameters. For this purpose the study considered dependent variable of agriculture GDP and several independent variables were contain major, minor crops, livestock and forestry. The empirical results indicate that agricultural sub-sectors contribute positively and significantly in the agriculture GDP. However, forestry sub-sector had expected sign but the variable was not significant. In agriculture, forestry sub-sector share was considered very poor compared with other sub-sectors could be due to less attention paid from the government. The results suggest that the Government of Pakistan should make some intervention in the agricultural sub-sectors by introducing innovative agriculture technologies that could improve the sub-sectors share in the overall agriculture GDP.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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