Bibliographic record
Abstract
the mother country-that grand old country from which we all hail.(Cheers.)I have watched his progress in life, and I find him now with not less earnestness, with not less enthusiasm, but with matured mind and with the experience that he has gained by long, intelligent, and vigilant observation of public affairs, now standing one of the first journalists in Canada (enthusiastic cheers), worthy of this demonstration, and worthy of the exertions which have been made for him by the true electors of Western Montreal.It is true that, he has told us, he is a defeated candidate, and no one more regrets that defeat than I do ; not only on my own account, but on account of the party of which, for the present at all events, I may be considered the leader (cheers).Mr. White has this consolation, that the loss is to his party, the great Conservative party, that the loss is to the City of Montreal (we know it) -that the loss is to myself who looked forward hopefully to having him acting with me, fighting with me, battling, as I said a few evenings ago, with the beasts at Ephesus.(Cheers.)But, in truth, it has been no defeat; it is a great triumph, for he had the real honest vote of West Montreal, and he has in this demonstration the testimony of the wealth, intelligence, enterprise and commerce of Montreal. (Cheers.)I might, gentlemen, at this late hour, content myself with making these remarks (No! no !!go on !
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 teacher head, 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".