Alternative dissertation formats in education-based doctorates
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The doctorate and doctoral writing remain popular areas of inquiry and discussion, and yet very little research has empirically investigated the trends in dissertation types and how these trends might indicate broader changes in dissertation writing practices. This article builds on our recent work that investigated the macrostructures and research designs of 1,373 education-based PhD dissertations from five major Canadian research universities. In this current article, we more deeply explore the emergence in popularity of two ‘alternative’ or non-traditional dissertation macrostructures in education fields: the manuscript-style dissertation and the topic-based PhD dissertation. We highlight the popularity of these two dissertation types as evidence of shifting notions of what doctoral research and dissertations can (and do) look like in contemporary PhD programs. We focus specifically on these two dissertation macrostructures that were prevalent in our analysis, yet which are scarcely addressed in education-based dissertation resources. We provide a deeper reflection on the popularity of these dissertation models from our large-scale study, the ways these types of dissertations are organized at the global (macrostructural) level, and the chosen research designs, number of chapters, word counts, and authorship status (as either single-authored, partially co-authored, or mostly co-authored texts).
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | Scholarly communication Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Other design | low |
| grok | Scholarly communication Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
| opus | Scholarly communication Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 it