Bibliographic record
Abstract
When oral culture becomes literate, in what way does human consciousness itself change? And how does the new form of communication affect the content and meaning of texts? In this book, one of the most original and penetrating thinkers in Greek studies describes the transformation from orality to literacy in classical times and reflects upon its continued meaning for us today. Fresh insights into the orality-literacy shift in human consciousness from one who has long been studying this shift in ancient Greece and has now brought his vast learning and reflections to bear on our own times. This book is for a wide audience and calls for thoroughly rethinking current views on language, thought, and society from classical scholarship through modern philosophy, anthropology, and poststructuralism.”Walter J. Ong All in all, we have in this book the summary statement of one of the great pioneers in the study of oral and literate culture, fascinating in its scope and rewarding in its sophistication. As have his other works, this book will contribute mightily to curing the biases resulting from our own literacy.”J. Peter Denny, Canadian Journal of Linguistics An extremely useful summary and extension of the revisionist thinking of Eric Havelock, whom most classicists and comparatists would rank among the premier classical scholars of the last three decades. . . . The book presents important (though controversial) ideas in. . . an available format.” Choice
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.019 |
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".