The Constitution of Bharat (DCMPT-2025): A Dharmic Constitutional Model of Plural Trusteeship for Future Generations
Bibliographic record
Abstract
This work presents The Constitution of Bharat (DCMPT-2025) — the world’s first Dharmic Constitutional Model of Plural Trusteeship. Drafted as a civilizational experiment in statecraft, it transcends the binaries of capitalism vs. socialism, secularism vs. sectarianism, nationalism vs. imperialism, by rooting governance in Dharma (the eternal moral order). Key innovations include: Dharma Index & Future Dharma Index: measurable audit tools for present and intergenerational justice. Trusteeship Economy: an alternative to capitalism and socialism, where wealth is held in sacred trust for society, nature, and future generations. Rights of Nature & Intergenerational Stakeholders: recognizing ecosystems and unborn generations as constitutional subjects. Dharmic Council & Dharma Bench: institutional guardians ensuring ethics, transparency, and cosmic balance in governance. Global Dharma Council: a proposed reform of the UN system, introducing ecological and intergenerational veto powers. Philosophically, this Constitution harmonizes Indic civilizational ethics (Hindu Dharma, Jain Ahimsa, Buddhist Karuṇā, Sikh Sevā, Indigenous Trusteeship Wisdom) with global traditions (Greek Logos, Confucian Li, African Ubuntu, Native American Seventh Generation Principle). Unlike conventional constitutions, this is both a national charter for Bharat and a constitutional offering to humanity — a framework to safeguard human dignity, ecological balance, technological ethics, and the rights of future generations. This document stands as a scholarly, future-proof constitutional vision — integrating law, ecology, ethics, and philosophy — and aims to inspire global debate on the foundations of governance in the 21st century and beyond.
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 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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".