Bibliographic record
Abstract
Full out the plug in order to get back to the physical body. —Marshall McLuhan, 19 December 1978 Four Years Before a Massive Stroke Took Away his Ability to Speak, Marshall McLuhan Advised his Son Eric To “Develop the power and habit of listening. It is not a power that I have, and nobody ever told me how to go about getting it.” A notorious talker who would “lecture and discourse nonstop if anyone else was present” (Marchand 273), and who frequently telephoned his friends and colleagues in the wee hours of the morning to discuss his latest idea, this English professor turned media theorist was also one of the first academics to recognize and seize the opportunities offered by the new media of popular culture to reach audiences wider than the readerships of scholarly journals. From the 1960s onward, McLuhan made dozens of appearances on radio and television and even made a cameo film appearance: in Woody Allen'sAnnie Hall, he silences an arrogant Columbia University professor by declaring, “You know nothing of my work.” At once a raconteur and an aphorist, he was most alive when processing his thoughts aloud to a live audience, whether in a Canadian Broadcasting Corporation recording studio, at his family dinner table, or in his office at the University of Toronto, where he dictated many of his later writings (books, articles, and correspondence) to his secretary, Margaret Stewart (“Marge”). “Telephone conversations with Marshall would turn into miniature symposia,” recalled the University of Toronto president Claude Bissell (qtd. in Nevitt 284). Ironically, given his own wee-hours use of the telephone, McLuhan theorized this medium of secondary (or electronic) orality as “an intensely personal form that ignores all the claims of visual privacy prized by literate man” and as “an irresistible intruder in time or place” (Understanding Media296).
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.038 | 0.022 |
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".