Guru ka Langar as Parsad Embracing "Sarve Dharm Sambhaw"
Bibliographic record
Abstract
The Food which is offered to Hindu deity is known as Parsad. This food after offering to deity is distributed among devotees as offering of God. There are few rules in India for preparing the food as Parsad. The whole research paper revolves around the idea behind the langar, as per the Sikh faith, is for people of all castes and religions to eat together before visiting the Guru1 Every human being is equal. ‘The concept of equality is visible everywhere, from the place where people stay around the Gurudwara complex to the ‘langar’ (a concept of free dining for every one). Skin color fades in front of goodness, and religion does not matter in the sea of humanity here 2. In the Gurudwara it is carrying out the for the overall welfare of people--irrespective of religion, caste, colour, gender or creed. Not only we citizens of India believe this system of serving people but also Canadian president3 Trudeau and his family members first went to to the Hall, where thousands of devotees partake langar (community food) and also do sewa (voluntary service). The Golden Temple's Langar Hall is the biggest community kitchen in the world. Langar is the main meal which is served all afternoon to every visitor, irrespective of their social standing or religious affiliation. In the earlier time Guru Nanak Dev Ji wanted to stress the idea that everyone is equal. Everyone shares the tasks of preparation, cooking, serving and cleaning. He said that4 this community kitchen is meant for providing food to all devotees, pilgrims and visitors. It is a symbol of equality, fraternity and brotherhood. It is here that the high and the low, the rich and the poor, the learned and the illiterate, the kings and the paupers, all share the same food sitting together in one row5.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.050 | 0.019 |
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".