Bibliographic record
Abstract
Background This article1 presents a reworked keynote address given at the “Many McLuhans” conference held at the University of Toronto in September 2018 on the occasion of UNESCO recognizing Marshall McLuhan’s library as part of its Memory of the World program.Analysis The article explores McLuhan as a reader and suggests that his greatest work might have been what he read rather than what he wrote. Conclusion and implications The library, as a genre, is one of the great media forms of modernity and antiquity and a marker of the fragility and majesty of the things that humans do with their large brains. Contexte Cet article consiste en la révision d’un discours principal donné au colloque « Many McLuhans » tenu en septembre 2018 à l’Université de Toronto, à l’occasion de la reconnaissance de la bibliothèque de Marshall McLuhan par l’UNESCO dans le contexte de son programme Mémoire du monde.Analyse L’article explore McLuhan en tant que lecteur et suggère que sa plus grande œuvre consiste en ce qu’il a lu plutôt qu’en ce qu’il a écrit.Conclusions et implications La bibliothèque, en tant que genre, est une des grandes formes médiatiques de l’Antiquité et de la modernité et une instance de la fragilité et de la majesté de ce que font les humains avec leurs grands cerveaux.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.004 |
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".