McLuhan: Motion: e-Motion: Towards a Soft Ontology of Media
Bibliographic record
Abstract
All tools set forces in motion. […] The machine has not separated us from nature; through it we have discovered a new nature never before surmised. El Lissitzky, ‘Nasci’, Merz 8-9 (1924) The new media are not bridges between man and nature: they are nature. McLuhan, Counterblast (1969) The human lives in that it bodies [leibt], and thus it is admitted into the open of space, and through this self-admittance it holds itself already from the outset in a relation to its fellow humans and things. Heidegger Kunst – Plastik – Raum (1964) While media theorists would agree on few fundamentals intrinsic to their field of study—starting with the definition of ‘media’—they would no doubt concur that media have an epistemological dimension. Whether it be McLuhan's notion of the media ‘environment’ (‘Educational Effects’, p. 402) or Kittler's concept of a ‘discourse network’, it can be argued that the effects of media are cognate with the Foucauldian episteme : they ‘determine’ our situation because they function in a Heideggerian manner as the pre-condition of what we can know and say ( die Sprache spricht, nicht der Mensch ) and they ‘are’ our situation (as Mitchell and Hansen would have it) because they operate ‘environmentally’ as our mediatic frame of reference. But is it possible to speak of an ontology of media? Kittler addresses this question in his 2009 article ‘Towards an Ontology of Media’ by invoking, at the outset, McLuhan's 1971 comment that ‘“philosophy systematically excludes techne from its meditations. Only natural and living forms are classified as hylo-morphic”’ (quoted in Kittler, p. 25). Kittler argues that the Canadian media theorist gets Aristotle's metaphysics wrong: ‘[w]e have good reason to suppose, quite to the contrary, that form and matter are categories stemming originally from technical things and more or less forcibly transferred […] to natural ones’ (‘Ontology’, p. 25). Kittler grants priority to technology rather than nature, arguing that McLuhan was suggesting the opposite. In fact, McLuhan is arguing that technology is nature: ‘[t]he literate Greeks abstracted visual order out of preliterate oral chaos and called their artifact “Nature” ( phusis ). […] In today's electric world, man becomes aware that this artificial “Nature” of the Greeks is an extension of himself, just as he is an extension of nature.’ Kittler acknowledges that ‘McLuhan's curious philological error,’ however, becomes ‘a historical truth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.058 | 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 teacher head, 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".