Bibliographic record
Abstract
No other question treated in Hind Swaraj , not even that of the lawyers, doctors and hospitals, has provoked as much controversy as has the question of machinery – in the current idiom, ‘technology’. Gandhi's thinking on machinery underwent gradual development, the main features of which are traced below. [Ed.] 1919 ‘There is thus room in the country for both the mill industry and the handloom weaving. So let mills increase as also spinning-wheels and handlooms. And I should think that these latter are no doubt machines. The handloom is a miniature weaving mill. The spinning-wheel is a miniature spinning-mill. I would wish to see such beautiful little mills in every home. But the country is fully in need of the hand-spinning and hand-weaving industry. Agriculturists in no country can live without some industry to supplement agriculture … Even if we have sufficient mills in the country to produce cloth enough for the whole country, we are bound to provide our peasantry, daily being more and more impoverished, with some supplementary industry, and that which can be suitable to crores of people is hand-spinning and hand-weaving. Opposition to mills or machinery is not the point. What suits our country is the point. I am not opposed to the movement of manufacturing machines in the country, nor to making improvements in machinery.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".