Bibliographic record
Abstract
reader : In the whole of our discussion, you have not demonstrated the necessity for education; we always complain of its absence among us. We notice a movement for compulsory education in our country. The Maharaja Gaekwar has introduced it in his territories. Every eye is directed towards them. We bless the Maharaja for it. Is all this effort, then, of no use? editor : If we consider our civilisation to be the highest, I have regretfully to say that much of the effort you have described is of no use. The motive of the Maharaja and other great leaders who have been working in this direction is perfectly pure. They, therefore, undoubtedly deserve great praise. But we cannot conceal from ourselves the result that is likely to flow from their effort. What is the meaning of education? If it simply means a knowledge of letters, it is merely an instrument, and an instrument may be well used or abused. The same instrument that may be used to cure a patient may be used to take his life, and so may a knowledge of letters. We daily observe that many men abuse it, and very few make good use of it, and, if this is a correct statement, we have proved that more harm has been done by it than good.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.435 | 0.298 |
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".