Indicators of Food Security in Various Economies of World
Bibliographic record
Abstract
Food security was a complex sustainable development issue, linked to health and nutrition. It was essential for sustainable economic development, environment, and trade. Many countries were facing food shortages and food distribution problems. This resulted in chronic and often widespread hunger in masses. All nations worldwide, including developed, developing and underdeveloped nations were taking initiatives at micro as well as at macro level to ensure food security. Food security was a complex condition and it had four dimensions – availability, access, utilization and stability. These dimensions were better understood when presented through a suite of indicators. The indicators of food security were analysed and it was found that climate change, government policies and interventions were the most challenging areas. The study was based on 150 research papers related to food security issue in underdeveloped, developing and developed nations. The research tried to embrace discussions related to food security across the globe into a single composition. The study has unveiled the important keywords related to indicators of food security like globalization, government policies and interventions, production technique, human development, PDS, hunger and poverty, hunger and malnutrition, farming technique, climate change, agriculture production, urbanization, health and human development, women empowerment, value chain policy, health and malnutrition etc. which would help policy makers to understand different issues related to policy making in a better way.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".