Bibliographic record
Abstract
I begin by saying thank you to historian and scholar, Colin Duquemin, for it was from his reference question about salt that my interest in this topic began. Also, I mention Eli MacLaren, candidate in the PhD Collaborative Program in Book History and Print Culture, University of Toronto, whose quip at the annual Conference of the Bibliographical Society of Canada in 2004 inspired the title for this thesis. The submission of this thesis marks the culmination of a number of years devoted to part-time studies. The work has been a pleasure for many reasons, not the least of which was the opportunity to experience a new program at Brock University, the Interdisciplinary MA in Popular Culture, with a truly fine faculty and staff. Any interdisciplinary department faces unique challenges because of the collaboration required in crossing over the traditional academic boundaries. Similarly, new programs require an added level of energy from faculty because of the unexplored terrain; nevertheless, these dedicated educators met those challenges and have been able to provide strong support and an ideal climate for learning. I would not, however, have been able to take on this added pursuit without the support of
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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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; both teacher heads agree on what is shown here.
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".