Lectures on Canada, illustrating its present position, and shewing forth its onward progress, and predictive of its future destiny.
Bibliographic record
Abstract
XIIIth BATTALION VOLUNTEER9, U. C, 4c., 4c, Ac.Sir, tdy and munificent 1'atron of worth and useful efforts, these Lectures upou Canada are respectfully dedicated to you -there being the further propriety in this, from your having been the friend who suggested to the accomplished Lecturer so patriotic and loyal a work, at such an appropriate time as that of the presentthe troubled state of this continent.The author, the late Mr. Charlea Bass, although a celebrity with widely acknowledged powers of literary composition, and a master in happy expression of thought, had never, until recently, attempted the character of a political writer or state-economic.A man of practical aspirations only, he left to others that high role in the drama of life, whose position it better suited, and confined himself to the one he bad assumed.In his latter days, however, responding to the prompti ad accomplished genius, he addressed I. the subjecl mphlet -the place which Canada, under srell leuiated to occupy among the nations.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.079 | 0.009 |
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".