Bibliographic record
Abstract
In 1952, a terminally ill Harold Innis asked his closest intellectual confidant, Tom Easterbrook, to teach his signature course on communications on his behalf. With Innis’s premature death, the course turned out to be both Innis’s final course and the first course on Innis. Alongside Edward Comor’s detailed Introduction, Easterbrook’s previously unknown lectures clarify aspects of Innisian scholarship that have been obscured, neglected, or forgotten. These include Easterbrook’s understanding that Innis applied his concept of bias more broadly than most realize, that through references to media Innis strategically sought to promote certain values, and that Innis had become increasingly interested in the role played by institutions such as language, law, and the nation. Given Easterbrook’s intimate understanding of Innis’s methodology and research trajectories, this book is a rich resource for anyone interested in Innis and the foundations of media ecology. "Edward Comor’s book is like a time machine that takes us on a trip to 1950s-era University of Toronto and to the final days of the late, great Harold Innis. It provides an intimate and detailed window into the research and teaching of a scholar widely considered to be a pioneer in the field of media ecology. This book is highly recommended and an essential read for all of those interested in the history of communications technology." —Ron Deibert, Professor of Political Science and Director of the University of Toronto’s Citizen Lab "Before his untimely death in 1952, Harold Innis wrote some of the most important works in communications studies in North America. In addition to his published scholarship, Innis presented his ideas to undergraduates at the University of Toronto through a course that his former PhD student Tom Easterbrook took over when his health failed. By assembling and contextualizing course materials and by drawing from conversations between Innis and Easterbrook during the preceding summer, Edward Comor gives scholars a fascinating window into Innis’s pedagogical approach, his end-of-life concerns, as well as what for Innis remained unfinished. Through Comor’s extensive introduction and the publication of Easterbrook’s lectures for the course, readers also will gain understanding as to how Innis communicated his ideas and how he was interpreted by students – both those in the class and Easterbrook." —Michael Stamm, Chair and Professor, Department of History, Michigan State University
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".