Bibliographic record
Abstract
reader : Is there any historical evidence as to the success of what you have called soul-force or truth-force? No instance seems to have happened of any nation having risen through soul-force. I still think that the evildoers will not cease doing evil without physical punishment. editor : The poet Tulsidas has said ‘Of religion, pity or love is the root, as egotism of the body. Therefore, we should not abandon pity so long as we are alive.’ This appears to me to be a scientific truth. I believe in it as much as I believe in two and two being four. The force of love is the same as the force of the soul or truth. We have evidence of its working at every step. The universe would disappear without the existence of that force. But you ask for historical evidence. It is, therefore, necessary to know what history means. The Gujarati equivalent means: ‘It so happened.’ If that is the meaning of history, it is possible to give copious evidence. But, if it means the doings of kings and emperors, there can be no evidence of soul-force or passive resistance in such history. You cannot expect silver-ore in a tin-mine. History, as we know it, is a record of the wars of the world, and so there is a proverb among Englishmen that a nation which has no history, that is, no wars, is a happy nation.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.107 | 0.059 |
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".