The New World of Republishing in Open Access: A View from the Author's Side
Bibliographic record
Abstract
In the United States, where scholars typically do not hold copyright to their published work, many essays they previously published are now available only from a journal publisher for a high access fee or from an out-of-print book. As twenty-first-century researchers seek overviews and coherent histories of the many fields of literary and cultural studies that emerged over the last three decades, how can older generations of scholars, who worked primarily in print venues, put previously published work into digitally accessible formats that will keep it in current conversations? And why might new scholars want to? The author describes a new mode of republishing one's past essays in open access online, as illustrated by her and her co-author's experience. They learned the nuts and bolts, and also discovered some pitfalls, of open access republishing, including obtaining permissions from corporate publishers, correcting PDF-to-Word conversions, identifying design elements helpful for online use, and marketing their own book.
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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.017 | 0.051 |
| Scholarly communication | 0.051 | 0.072 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".