Internships and the PhD: Is This the Future Direction of Work-Integrated Learning in Australia?.
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
In the ten years since Australia's first large-scale scoping study of Work-Integrated Learning (WIL) there has been a rapid increase in WIL research and undergraduate WIL opportunities. Though well-established in undergraduate degrees, WIL in postgraduate research degrees is relatively unexplored. Less than half of PhD graduates in Australia are employed by the higher education sector, therefore transferable skills and industry experience are increasingly important. The last few years have seen several Australian peak bodies call for further investment in the employability of PhD graduates. The Australian Government recently provided funding aimed at encouraging doctoral students to undertake internships and placements. Drawing on seven qualitative interviews with past and present PhD students at Griffith University, this exploratory paper explores how PhD students view the potential role of WIL in higher degree research programs in Australia and the challenges they see as facing the broader implementation of WIL across PhD programs. This has broader implications for how WIL may be utilized to equip doctoral graduates with the industry experience and training to improve their employability outside the higher education sector.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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