Socialization and Social Capital in Online Doctoral Programs
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
Online doctoral programs are gaining in popularity, both among students and institutions. However, research to date on the effectiveness and popularity of such programs has looked largely at either measures of student satisfaction or of administrative effectiveness and design. Further, previous research has also tended to focus on the early part of doctoral study, particularly coursework. This mixed method study, conducted on three different programs within in a department of educational research in one university in UK will contribute to the literature in two important ways. First, it will look specifically on current and recently graduated student experiences from of the thesis component of the doctoral program using a demographic and experiential survey and following up with more in depth interviews to better understand students' motivation and goals for enrolling in their program and what kinds of academic experiences and knowledge they both bring to, and receive from, their program. Second, we will analyse the data through two lenses, that of academic socialization to help identify how academic identity changes over time, and that of social capital to help us understand the individual trajectories of students through their programs. Results will contribute both theoretically and practically to our understanding of student experience of the thesis process in online doctoral programs.
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.
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 | 0.000 | 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 | 0.000 | 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 it