Modernism’s “Doors of Perception”: From Ezra Pound’s Ideogrammic Method to Marshall Mcluhan’s “Mosaic”
Bibliographic record
Abstract
Writing to Ezra Pound in May 1948, Marshall McLuhan told the poet that, "we [that is, Hugh Kenner and I] have long taken a serious interest [in] your work."And so, McLuhan along with Kenner visited Pound at St Elizabeths in June 1948.The rest makes for interesting modernist literary and cultural studies history.This paper argues that McLuhan's method of composition, which he called a "mosaic," derives from his understanding of Pound's poetics of the ideogrammic method.In The Gutenberg Galaxy: The Making of Typographic Man (1962), McLuhan explains that the book "develops a mosaic or field approach to its problems.Such a mosaic image of numerous data and quotations in evidence offers the only practical means of revealing the causal operations in history."McLuhan learned much from the American poet, including to view literature/pedagogy as "training of perception"; and both developed texts that placed readers in media res, encouraging an heuristic approach to "reading" whereby readers are empowered to arrive at their own meaning or interpretation irrespective of the writers' ideology and/or agenda.Using examples from The Cantos and The Medium is the Massage: An Inventory of Effects (1967), this essay also probes the relationships between modernist aesthetics, technological prophesy and sociopolitical praxis.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.053 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".