Phd careers beyond the traditional: integrating individual and structural factors for a richer account
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
More than half of PhD graduates work outside academia. Yet we know little of the nature of their post-PhD careers and the conditions influencing them. Further, research to date tends to focus on either individual factors (e.g., graduate perceptions of PhD skills used) or structural factors (e.g., organizational interest in hiring PhDs). Few studies examine the intersection between individual and structural factors that actually influences career trajectories. Thus, this study was an exploratory examination of UK and Swiss non-traditional PhD careers in which we conceptually and empirically linked structural factors to individual experiences. The results provide a richer, more nuanced picture of PhD career trajectories, showing, for instance, how structural factors like distinct national economic climate and employment patterns intersected with individual factors like job-seeking strategies and job selection. The study’s originality lies in a narrative cross-case approach that merged empirical evidence from interviews with secondary data. We conclude by assessing the value of using such an integrative framework as well as suggesting areas for future research.
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 | 0.001 | 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 | 0.001 | 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) | 0.001 | 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