Who Are the Doctoral Students Who Drop Out? Factors Associated with the Rate of Doctoral Degree Completion in Universities
Why this work is in the frame
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Bibliographic record
Abstract
The issue of considerable dropout rate in doctoral programs is well documented across a large number of countries. However, few studies address the factors associated with doctoral completion among Non-U.S. countries, multiple universities and fields of research. Nor do they investigate the interactions between these factors. The present paper aimed to overcome these limitations and analyzed the population of doctoral students in all disciplines of the two largest universities of the French-speaking Community of Belgium (N = 1509). Specifically, we focused on several factors: gender, nationality, marital status, master grade, whether students continued at the same university when transitioning to the doctoral degree, whether they continued in the same field, age at registration, research field and funding (i.e., type of funding and associated job requirements). Findings indicate that four factors (marital status, master grade, research field and funding) are directly associated with dropout rate when all factors are considered jointly in the same model. Furthermore, results indicate that some of these factors, such as the marital status and gender, interact. In addition, we found that an accumulation of risk factors leads to a massive increase in dropout rates. Finally, a time course analysis revealed that the highest dropout rate occurs during the first two years and is related to the absence of funding or scholarship. The results, limits and futures perspectives are discussed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it