Bibliographic record
Abstract
P ayment of members by the State was the great question under debate in the Lower House during much of the time I spent in Melbourne, and, in spite of all the efforts of the Victorian democracy, the bill was lost. The objection taken at home, that payment degrades the House in the eyes of the people, could never arise in a new country, where a practical nation looks at the salaries as payment for work done, and obstinately refuses to believe in the work being clone without payment in some shape or other. In these colonies, the reasons in favour of payment are far stronger than they are in Canada or America, for while there country or town share equally the difficulties of finding representatives who will consent to travel hundreds and thousands of miles to Ottawa or Washington; in the Australias, Parliament sits in towns which contain from one-sixth to one-fourth of the whole population, and under a non-payment system power is thrown entirely into the hands of Melbourne, Sydney, Perth, Brisbane, Adelaide, and Hobarton. Not only do these cities return none but their own citizens, but the country districts, often unable to find within their limits men who have sufficient time and money to be able to attend throughout the sessions at the capital, elect the city traders to represent them.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".