Looking at Regulatory Mechanism of India's Public Distribution System Through Food Security Lens
Bibliographic record
Abstract
India’s largest food security programme i.e. Public Distribution System (PDS) is being governed and regulated by Public Distribution System (Control) order, 2001 which was subsequently amended in the years 2004 and 2015. In 2015 it transformed into Targeted Public Distribution System (Control) order. Providing legality to such a gigantic programme is intended for its effective implementation. Public Distribution System aims to provide food to the population below poverty line at highly subsidised prices. This Indian Government’s prestigious programme involves a massive population, highest food subsidy bills to country’s exchequer. This enforcement has a huge role in providing fair stake to food to every poor person in the country. This order has provisions for supply and distribution, price control and fair access to food grains. It resulted in availability of food grains to millions of poor people at an affordable price. However, there was a change in philosophy with respect to provisioning of food grains with the enactment of the National Food Security Act 2013, since before this Act the supply of food grains under PDS was treated as a welfare measure only. After this legislation, the beneficiaries secured a legal right to get the food at a fair price through the PDS. Presently in most of the states the PDS is being regulated by both TPDS (Control) Order, 2015 and National Food Security Act, 2013. However, it was criticised for its inefficient beneficiary identification like higher error of inclusion of ineligible beneficiaries and exclusion of eligible beneficiaries and leakages in the entire supply chain and quality of food grains. This paper examines different provisions of the regulatory mechanisms that are governing the PDS in food security angle. It relies on secondary research along with, focus group discussions with the stakeholders. It will be discussed in detail with case study of Indian state of Telangana. Section 3(1) of NFSA ensures five kilograms of food grains per person per month which definitely meet the carbohydrate requirement of the population. However, it may not ensure nutritional security because the poor are not entitled for the protein diet. It is statutory to cover up to 75% of rural population and 50% of urban population under NFSA. In the instances like war, flood, severe drought where the states are not in a position to supply food grains, this act has a provision to provide food subsidy allowance which indirectly ensures food security to the poor. Digitization of all the PDS beneficiaries, “Aadhaar” seeding, end to end computerization of PDS would reduce the leakages in the system which indirectly benefits the poor in accessing the right amount of food to which they are entitled to.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".