Bibliographic record
Abstract
reader : From your views I gather that you would form a third party. You are neither an extremist nor a moderate. editor : That is a mistake. I do not think of a third party at all. We do not all think alike. We cannot say that all the moderates hold identical views. And how can those who want to serve only, have a party? I would serve both the moderates and the extremists. Where I should differ from them, I would respectfully place my position before them, and continue my service. reader : What, then, would you say to both the parties? editor : I would say to the extremists: – ‘I know that you want Home Rule for India; it is not to be had for your asking. Everyone will have to take it for himself. What others get for me is not Home Rule but foreign rule; therefore, it would not be proper for you to say that you have obtained Home Rule, if you expelled the English. I have already described the true nature of Home Rule. This you would never obtain by force of arms. Brute force is not natural to the Indian soil. You will have, therefore, to rely wholly on soul-force. You must not consider that violence is necessary at any stage for reaching our goal.’
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.286 | 0.175 |
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".