Socio-Economic Characteristics of Farming Community and Food Security Situation in Punjab, Pakistan
Bibliographic record
Abstract
Despite the availability of ample food and reasonably low food prices, food insecurity prevailed in many developing countries in 1970s. The paradigm shift in 1980s from supply to demand side of food security underlined the entitlement or access to food as the center of mainstream research. Current study is the findings of the data collected from household level survey regarding socio-economic and food insecurity conditions in the Punjab province of Pakistan. The descriptive analysis and cross tabulation of the household data revealed that household assets, house building material, size of agricultural farms, ownership of tractor, farm livestock were associated with food security conditions of the farming community. The data results also confirmed that the poorer families made major expenditure on the food out of total household expenditure every month. It was also revealed that households in the irrigated regions of Punjab have better entitlement as compared with households surveyed from Thal (desert) and rain-fed regions. The daily consumption of eggs, milk and various forms of meat was found below daily recommended nutritional requirements in most of the households. This study confirms the findings of the earlier surveys made in this regard and highlights the demand side of food insecurity issues in Punjab province of Pakistan. Food security policies in Pakistan should focus entitlement and food access of farming households. The household and farm assets need to be built for reducing vulnerability of poorer farming community to food insecurity in Pakistan.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".