Bibliographic record
Abstract
The bibliographical search that brought this company of travellers together began in the Lingabibliothek at the University of Hamburg and, on the other end of furtive dashes through an alien countryside, in the library of the Iberoamerikanisches Insthut in West Berlin.Copies of a good number of the account were put in jeopardy one night by a border guard of the German Democratic Republic who insisted on unravelling the microfilm and examining it against a streetlight to see if it contained pornography.My thanks to the librarians at those two magnificent institutions, who helped me assemble the core of the material and copy it, as well as others at the Library of Congress, the library of Tulane University, and the library of my own University of British Columbia, who helped to enlarge the company of writers that was to be followed along the Veracruz-Jalapa road, and to obtain background material on them.The analysis was made possible by several grants from the Social Sciences and Humanities Research Council of Canada, as well as smaller grants and several periods of leave from the University of British Columbia.The publication of this book has been facilitated by a subvention from the Social Science Federation of Canada.Elizabeth Krupp helped in the early processing of the manuscripts.Various drafts were typed by Elizabeth Maclnnes, Diana Phillips, and Irene Hull, who also assisted in early editing.Later versions were stored and revised at Jeeva's Word Processing.Paul Jantz, Angus Weller, and his associates, Grettchen Zdorkowsky and Robert Laird worked on the preparation of maps, photographs, and drawings.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.357 | 0.151 |
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; the direct Gemma label and the distilled Codex classifier 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".