Bibliographic record
Abstract
Marshal McLuhan, the Canadian medium guru and Edward T. Hall, the distinguished American anthropologist, are two intellectual giants of the 20th century. Each of them has, in his own way, set up a completely new outlook on our life and a new way of experiencing the world around us. Though working in different fields of study, these two great masters think very much alike. Both of them seem to have profound insight and penetrating perception in unveiling the true relationship between man and his environment. They both regard man’s technological creations as extensions of man and recognize the immense power of media in shaping and reorganizing human life; they have been searching for basic rules and patterns in media forms rather than in the content; they both recognized the psychic and social consequences of media or extensions of man. But each of them deals with human extensions from different perspectives and focuses on different aspects of human life. McLuhan seems to be more interested in the life of forms and their surprising modalities, while Hall concerns more about cultural forms or how environment variations bring about different life patterns in different cultures. Together they have led us to see both the forest and the tree in the multicultural global village. By comparing these two geniuses, we can better understand their epoch-making ideologies and thus better understand ourselves and the world around us. What we can benefit from this comparison is, besides the enlightening ideas and discoveries, a rethinking of our own research approach and way of perceiving the world. It is time for us to stop being distracted by the superficial content of things and begin to look for the truth in the things themselves and in their own cultural contexts. Only in this way can we find true nature of human man communication and human relationships.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.025 |
| Scholarly communication | 0.011 | 0.022 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".