McLuhan, Burawoy, McLuhan: Extending Anthropic Communications On the Human Equation, the Extended Case Method and Human Extension
Bibliographic record
Abstract
One of the main contributions that Marshall McLuhan made to the fields of culture, technology and communication was the idea of ‘the extensions of man,’ the subtitle of his masterpiece “Understanding Media” (1964). Here the idea of ‘human extension’ is explored for application in\nhuman-social sciences, along with the notion of ‘the extended case method’ promoted by current President of the International Sociological Association, Michael Burawoy with its origins in the Manchester School of Social Anthropology. ‘Human extension’ is offered as an alternative approach to the ‘evolution’ of artefacts and\nis connected to the communications works of Marshall and his son Eric, reaching to the recent idea of a general ‘human equation.’\nKeywords\nMarshall McLuhan, Michael Burawoy, Eric McLuhan,\nHuman Extension, Extended Case Method, Human\nEquation, Toronto School of Communications,\nAnthropic-Social Science, Natural-Physical Science,\nSteve Fuller, Innovation Diffusion, Extension Theory,\nDehumanization and Re-Humanization, Tetradic\nApproach, Eden-in-Reverse
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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 | 0.018 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.006 | 0.034 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".