Agricultural Productivity in Balochistan Province of Pakistan A Geographical Analysis
Bibliographic record
Abstract
Agricultural sector plays a leading role in Pakistan’s economy. It contributed to nearly one fifth of the national GDP in 2010. Agricultural productivity is regions dependent, demanding further investigation. This study examines the productivity index in districts of Balochistan province of Pakistan from 1981-82 to 2008-2009. Besides the thermal and water regime, pedological conditions play a favorable role in growing of valuable crops. The food crops, wheat, rice, bajra, barley jowar and maize have been selected for the study. By contrast, very low level of agricultural productivity is confined to the districts falling in the drought prone areas characterized by irregular rainfall, rugged topography and poor irrigation facilities. Inadequacy of water is the main hurdle in agricultural productivity. For the present investigation, district wise secondary data have been collected from the agricultural census of Balochistan. The data collected have been processed and Yield Coefficient method has been employed to find out the level of agricultural productivity. The results are depicted by choropleth method on map. Hence, in the present paper an attempt has been made to assess the regional disparities in levels of agricultural productivity in districts of Balochistan province. Identification of causes of the disparity can prove helpful in solving the problem, thus enabling solution of food security.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".