Bibliographic record
Abstract
From his first reflections on advertising as a ‘magical institution’ in 1952 to his last writings on ‘The Brain and Media’ in 1978, Marshall McLuhan was reproached for his utopian view of media technologies as the ‘extensions of man’ and for his failure to understand the new, more formidable rhetorical powers of the electric mass media. These criticisms are not entirely unjust. At times McLuhan does seem to view media machines as vehicles of flight into a ‘cosmic harmony’ that ‘transcends space and time’. But for all his ‘delirious tribal optimism’ (Baudrillard), McLuhan also understood that the global village or ‘global theatre’ has become a theatre of war, a staging area for ‘colossal violence’ and ‘maximal conflict’. In order to shed new light on this darker, more radical vision of the mass media set forth by McLuhan, this article explores his decisive – but largely unacknowledged – contribution to radical media studies today, especially to the work of Paul Virilio, Friedrich Kittler and others concerned with the alliance of war, media and information in modern society. After some reflections on McLuhan's ‘mosaic’ approach to the media ecology and his view of media as the extensions of man, I examine three modulations of his most infamous aphorism: the medium is the message; the medium is the massage; and the medium is the mass-age.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.025 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".