Dissertation-to-Book Publication Patterns Among a Sample of R1 Institutions
Bibliographic record
Abstract
INTRODUCTION A common concern about openly available electronic theses and dissertations is that their “openness” will prevent graduate student authors from publishing their work commercially in the future. A handful of studies have explored aspects of this topic; this study reviewed dissertation-to-book publication patterns at Carnegie Classification R1 academic institutions. METHODS This study analyzed over 23,000 dissertations from twelve U.S. universities to determine how frequently dissertations were subsequently published as books matching the original dissertation in pagination, chapters, and subject matter. WorldCat and several other resources were used to make publication determinations. RESULTS Across the sample set, a very small percentage of dissertations were published as books that matched the original dissertation on pagination, chapters, and subject matter. The average number of years for dissertations in the study to be published as books was determined for broad subject categories and for select academic disciplines. Results were compared across public and private institutions, and books that were self-published or published by questionable organizations were identified. DISCUSSION Dissertation-to-book trends occur primarily in the social sciences, humanities, and arts. With dissertations for which the author is actively working to publish as a book, the commonly offered 6- to 24-month embargo periods appear sufficient, provided that extensions or renewals continue to be available. CONCLUSION This study has implications for librarians providing services to graduate students, faculty advisors, and graduate colleges/schools in regard to dissertation embargo lengths, self-publishing, and what we have termed questionable publishers, as these areas continue to provide opportunities for librarians to educate these stakeholders.
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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 | 0.012 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.028 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.002 | 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; 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".