Bibliographic record
Abstract
Monsieur Michael Heaney de l'IFLA, Directeur général du Service des bibliothèques de l'Université d'Oxford (R.-U.)Mesdames, Messieurs, Bonjour, Je tiens tout d'abord à vous souhaiter la bienvenue à Montréal.J'espère que les travaux que vous mènerez ici seront productifs, et qu'ils vous laisseront aussi quelques moments pour profiter de notre ville -si bien sûr vous n'avez pas oublié d'apporter un peu de beau temps dans vos bagages … L'histoire de nos bibliothèques publiques à Montréal n'a pas toujours été facile.Mais, au cours des dernières années, la communauté montréalaise a réalisé l'importance tout à fait centrale de ces institutions, dans une région qui compte de plus en plus sur l'économie du savoir et sur les compétences culturelles de sa population pour prendre sa place dans le réseau des grandes villes du monde.For quite a long time, we in Montreal relied first and foremost on our exceptional location on this new continent to promote our economic growth and the metropolitan influence of our city.This wasn't a bad idea after all, as we succeeded in establishing a very dynamic commercial and industrial center where ocean liners coming from Europe met railroad networks that converged into our large inland port.But this model met its limits, first with the economic transformation of North America, and second with the emergence of a radically different paradigm for the growth of the global economy.We came to realize that the main drive for our development, and for the quality of our urban life, depended more and more on the abilities of our people, rather than from mere geography and trading routes.This realization has led to a genuine change of paradigm in the way we understand our city, assess its full potential, and draw our roadmap into the future.Les grandes infrastructures qui ont donné son essor initial à Montréal ont admirablement réussi leur travail.Notre port, notre réseau ferroviaire et nos équipements de transbordement ont alimenté nos premières générations d'industries et
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.645 | 0.509 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".